diff --git a/Cargo.lock b/Cargo.lock
index 1a8bc134b3..c8d09c7b3e 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -25,9 +25,9 @@ checksum = "aae1277d39aeec15cb388266ecc24b11c80469deae6067e17a1a7aa9e5c1f234"
 
 [[package]]
 name = "ahash"
-version = "0.7.7"
+version = "0.7.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5a824f2aa7e75a0c98c5a504fceb80649e9c35265d44525b5f94de4771a395cd"
+checksum = "891477e0c6a8957309ee5c45a6368af3ae14bb510732d2684ffa19af310920f9"
 dependencies = [
  "getrandom",
  "once_cell",
@@ -36,9 +36,9 @@ dependencies = [
 
 [[package]]
 name = "ahash"
-version = "0.8.7"
+version = "0.8.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "77c3a9648d43b9cd48db467b3f87fdd6e146bcc88ab0180006cef2179fe11d01"
+checksum = "e89da841a80418a9b391ebaea17f5c112ffaaa96f621d2c285b5174da76b9011"
 dependencies = [
  "cfg-if",
  "getrandom",
@@ -49,9 +49,9 @@ dependencies = [
 
 [[package]]
 name = "aho-corasick"
-version = "1.1.2"
+version = "1.1.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b2969dcb958b36655471fc61f7e416fa76033bdd4bfed0678d8fee1e2d07a1f0"
+checksum = "8e60d3430d3a69478ad0993f19238d2df97c507009a52b3c10addcd7f6bcb916"
 dependencies = [
  "memchr",
 ]
@@ -119,9 +119,9 @@ dependencies = [
 
 [[package]]
 name = "anstream"
-version = "0.6.11"
+version = "0.6.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6e2e1ebcb11de5c03c67de28a7df593d32191b44939c482e97702baaaa6ab6a5"
+checksum = "d96bd03f33fe50a863e394ee9718a706f988b9079b20c3784fb726e7678b62fb"
 dependencies = [
  "anstyle",
  "anstyle-parse",
@@ -133,9 +133,9 @@ dependencies = [
 
 [[package]]
 name = "anstyle"
-version = "1.0.4"
+version = "1.0.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7079075b41f533b8c61d2a4d073c4676e1f8b249ff94a393b0595db304e0dd87"
+checksum = "8901269c6307e8d93993578286ac0edf7f195079ffff5ebdeea6a59ffb7e36bc"
 
 [[package]]
 name = "anstyle-parse"
@@ -184,9 +184,9 @@ dependencies = [
 
 [[package]]
 name = "argminmax"
-version = "0.6.1"
+version = "0.6.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "202108b46429b765ef483f8a24d5c46f48c14acfdacc086dd4ab6dddf6bcdbd2"
+checksum = "52424b59d69d69d5056d508b260553afd91c57e21849579cd1f50ee8b8b88eaa"
 dependencies = [
  "num-traits",
 ]
@@ -221,9 +221,9 @@ dependencies = [
 
 [[package]]
 name = "assert_cmd"
-version = "2.0.13"
+version = "2.0.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "00ad3f3a942eee60335ab4342358c161ee296829e0d16ff42fc1d6cb07815467"
+checksum = "ed72493ac66d5804837f480ab3766c72bdfab91a65e565fc54fa9e42db0073a8"
 dependencies = [
  "anstyle",
  "bstr",
@@ -253,18 +253,18 @@ checksum = "16e62a023e7c117e27523144c5d2459f4397fcc3cab0085af8e2224f643a0193"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
 name = "async-trait"
-version = "0.1.77"
+version = "0.1.79"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c980ee35e870bd1a4d2c8294d4c04d0499e67bca1e4b5cefcc693c2fa00caea9"
+checksum = "a507401cad91ec6a857ed5513a2073c82a9b9048762b885bb98655b306964681"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -284,9 +284,9 @@ checksum = "9ae037714f313c1353189ead58ef9eec30a8e8dc101b2622d461418fd59e28a9"
 
 [[package]]
 name = "autocfg"
-version = "1.1.0"
+version = "1.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d468802bab17cbc0cc575e9b053f41e72aa36bfa6b7f55e3529ffa43161b97fa"
+checksum = "f1fdabc7756949593fe60f30ec81974b613357de856987752631dea1e3394c80"
 
 [[package]]
 name = "avro-schema"
@@ -304,9 +304,9 @@ dependencies = [
 
 [[package]]
 name = "backtrace"
-version = "0.3.69"
+version = "0.3.71"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2089b7e3f35b9dd2d0ed921ead4f6d318c27680d4a5bd167b3ee120edb105837"
+checksum = "26b05800d2e817c8b3b4b54abd461726265fa9789ae34330622f2db9ee696f9d"
 dependencies = [
  "addr2line",
  "cc",
@@ -355,22 +355,22 @@ dependencies = [
 
 [[package]]
 name = "bindgen"
-version = "0.68.1"
+version = "0.69.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "726e4313eb6ec35d2730258ad4e15b547ee75d6afaa1361a922e78e59b7d8078"
+checksum = "a00dc851838a2120612785d195287475a3ac45514741da670b735818822129a0"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "cexpr",
  "clang-sys",
+ "itertools 0.12.1",
  "lazy_static",
  "lazycell",
- "peeking_take_while",
  "proc-macro2",
  "quote",
  "regex",
  "rustc-hash",
  "shlex",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -396,9 +396,9 @@ checksum = "bef38d45163c2f1dde094a7dfd33ccf595c92905c8f8f4fdc18d06fb1037718a"
 
 [[package]]
 name = "bitflags"
-version = "2.4.2"
+version = "2.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ed570934406eb16438a4e976b1b4500774099c13b8cb96eec99f620f05090ddf"
+checksum = "cf4b9d6a944f767f8e5e0db018570623c85f3d925ac718db4e06d0187adb21c1"
 dependencies = [
  "serde",
 ]
@@ -432,9 +432,9 @@ dependencies = [
 
 [[package]]
 name = "borsh"
-version = "1.3.1"
+version = "1.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f58b559fd6448c6e2fd0adb5720cd98a2506594cafa4737ff98c396f3e82f667"
+checksum = "0901fc8eb0aca4c83be0106d6f2db17d86a08dfc2c25f0e84464bf381158add6"
 dependencies = [
  "borsh-derive",
  "cfg_aliases",
@@ -442,15 +442,15 @@ dependencies = [
 
 [[package]]
 name = "borsh-derive"
-version = "1.3.1"
+version = "1.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7aadb5b6ccbd078890f6d7003694e33816e6b784358f18e15e7e6d9f065a57cd"
+checksum = "51670c3aa053938b0ee3bd67c3817e471e626151131b934038e83c5bf8de48f5"
 dependencies = [
  "once_cell",
  "proc-macro-crate",
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
  "syn_derive",
 ]
 
@@ -462,9 +462,9 @@ checksum = "ada7f35ca622a86a4d6c27be2633fc6c243ecc834859628fcce0681d8e76e1c8"
 
 [[package]]
 name = "brotli"
-version = "3.4.0"
+version = "3.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "516074a47ef4bce09577a3b379392300159ce5b1ba2e501ff1c819950066100f"
+checksum = "d640d25bc63c50fb1f0b545ffd80207d2e10a4c965530809b40ba3386825c391"
 dependencies = [
  "alloc-no-stdlib",
  "alloc-stdlib",
@@ -483,9 +483,9 @@ dependencies = [
 
 [[package]]
 name = "bstr"
-version = "1.9.0"
+version = "1.9.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c48f0051a4b4c5e0b6d365cd04af53aeaa209e3cc15ec2cdb69e73cc87fbd0dc"
+checksum = "05efc5cfd9110c8416e471df0e96702d58690178e206e61b7173706673c93706"
 dependencies = [
  "memchr",
  "regex-automata",
@@ -494,9 +494,9 @@ dependencies = [
 
 [[package]]
 name = "bumpalo"
-version = "3.14.0"
+version = "3.16.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7f30e7476521f6f8af1a1c4c0b8cc94f0bee37d91763d0ca2665f299b6cd8aec"
+checksum = "79296716171880943b8470b5f8d03aa55eb2e645a4874bdbb28adb49162e012c"
 
 [[package]]
 name = "byte-unit"
@@ -511,9 +511,9 @@ dependencies = [
 
 [[package]]
 name = "bytecheck"
-version = "0.6.11"
+version = "0.6.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8b6372023ac861f6e6dc89c8344a8f398fb42aaba2b5dbc649ca0c0e9dbcb627"
+checksum = "23cdc57ce23ac53c931e88a43d06d070a6fd142f2617be5855eb75efc9beb1c2"
 dependencies = [
  "bytecheck_derive",
  "ptr_meta",
@@ -522,9 +522,9 @@ dependencies = [
 
 [[package]]
 name = "bytecheck_derive"
-version = "0.6.11"
+version = "0.6.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a7ec4c6f261935ad534c0c22dbef2201b45918860eb1c574b972bd213a76af61"
+checksum = "3db406d29fbcd95542e92559bed4d8ad92636d1ca8b3b72ede10b4bcc010e659"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -539,22 +539,22 @@ checksum = "e1e5f035d16fc623ae5f74981db80a439803888314e3a555fd6f04acd51a3205"
 
 [[package]]
 name = "bytemuck"
-version = "1.14.1"
+version = "1.15.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ed2490600f404f2b94c167e31d3ed1d5f3c225a0f3b80230053b3e0b7b962bd9"
+checksum = "5d6d68c57235a3a081186990eca2867354726650f42f7516ca50c28d6281fd15"
 dependencies = [
  "bytemuck_derive",
 ]
 
 [[package]]
 name = "bytemuck_derive"
-version = "1.5.0"
+version = "1.6.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "965ab7eb5f8f97d2a083c799f3a1b994fc397b2fe2da5d1da1626ce15a39f2b1"
+checksum = "4da9a32f3fed317401fa3c862968128267c3106685286e15d5aaa3d7389c2f60"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -565,9 +565,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
 
 [[package]]
 name = "bytes"
-version = "1.5.0"
+version = "1.6.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a2bd12c1caf447e69cd4528f47f94d203fd2582878ecb9e9465484c4148a8223"
+checksum = "514de17de45fdb8dc022b1a7975556c53c86f9f0aa5f534b98977b171857c2c9"
 
 [[package]]
 name = "bytesize"
@@ -609,9 +609,9 @@ dependencies = [
 
 [[package]]
 name = "cc"
-version = "1.0.83"
+version = "1.0.92"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f1174fb0b6ec23863f8b971027804a42614e347eafb0a95bf0b12cdae21fc4d0"
+checksum = "2678b2e3449475e95b0aa6f9b506a28e61b3dc8996592b983695e8ebb58a8b41"
 dependencies = [
  "jobserver",
  "libc",
@@ -661,9 +661,9 @@ dependencies = [
 
 [[package]]
 name = "chrono"
-version = "0.4.35"
+version = "0.4.37"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8eaf5903dcbc0a39312feb77df2ff4c76387d591b9fc7b04a238dcf8bb62639a"
+checksum = "8a0d04d43504c61aa6c7531f1871dd0d418d91130162063b789da00fd7057a5e"
 dependencies = [
  "android-tzdata",
  "iana-time-zone",
@@ -686,9 +686,9 @@ dependencies = [
 
 [[package]]
 name = "chrono-tz"
-version = "0.8.5"
+version = "0.8.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "91d7b79e99bfaa0d47da0687c43aa3b7381938a62ad3a6498599039321f660b7"
+checksum = "d59ae0466b83e838b81a54256c39d5d7c20b9d7daa10510a242d9b75abd5936e"
 dependencies = [
  "chrono",
  "chrono-tz-build",
@@ -729,18 +729,18 @@ dependencies = [
 
 [[package]]
 name = "clap"
-version = "4.4.18"
+version = "4.5.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1e578d6ec4194633722ccf9544794b71b1385c3c027efe0c55db226fc880865c"
+checksum = "90bc066a67923782aa8515dbaea16946c5bcc5addbd668bb80af688e53e548a0"
 dependencies = [
  "clap_builder",
 ]
 
 [[package]]
 name = "clap_builder"
-version = "4.4.18"
+version = "4.5.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4df4df40ec50c46000231c914968278b1eb05098cf8f1b3a518a95030e71d1c7"
+checksum = "ae129e2e766ae0ec03484e609954119f123cc1fe650337e155d03b022f24f7b4"
 dependencies = [
  "anstream",
  "anstyle",
@@ -751,15 +751,15 @@ dependencies = [
 
 [[package]]
 name = "clap_lex"
-version = "0.6.0"
+version = "0.7.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "702fc72eb24e5a1e48ce58027a675bc24edd52096d5397d4aea7c6dd9eca0bd1"
+checksum = "98cc8fbded0c607b7ba9dd60cd98df59af97e84d24e49c8557331cfc26d301ce"
 
 [[package]]
 name = "clipboard-win"
-version = "5.2.0"
+version = "5.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "12f9a0700e0127ba15d1d52dd742097f821cd9c65939303a44d970465040a297"
+checksum = "d517d4b86184dbb111d3556a10f1c8a04da7428d2987bf1081602bf11c3aa9ee"
 dependencies = [
  "error-code",
 ]
@@ -779,6 +779,18 @@ version = "1.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "acbf1af155f9b9ef647e42cdc158db4b64a1b61f743629225fde6f3e0be2a7c7"
 
+[[package]]
+name = "comfy-table"
+version = "7.1.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b34115915337defe99b2aff5c2ce6771e5fbc4079f4b506301f5cf394c8452f7"
+dependencies = [
+ "crossterm",
+ "strum",
+ "strum_macros 0.26.2",
+ "unicode-width",
+]
+
 [[package]]
 name = "compact_str"
 version = "0.7.1"
@@ -813,9 +825,9 @@ dependencies = [
 
 [[package]]
 name = "const-random"
-version = "0.1.17"
+version = "0.1.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5aaf16c9c2c612020bcfd042e170f6e32de9b9d75adb5277cdbbd2e2c8c8299a"
+checksum = "87e00182fe74b066627d63b85fd550ac2998d4b0bd86bfed477a0ae4c7c71359"
 dependencies = [
  "const-random-macro",
 ]
@@ -893,18 +905,18 @@ checksum = "ccaeedb56da03b09f598226e25e80088cb4cd25f316e6e4df7d695f0feeb1403"
 
 [[package]]
 name = "crc32fast"
-version = "1.3.2"
+version = "1.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b540bd8bc810d3885c6ea91e2018302f68baba2129ab3e88f32389ee9370880d"
+checksum = "b3855a8a784b474f333699ef2bbca9db2c4a1f6d9088a90a2d25b1eb53111eaa"
 dependencies = [
  "cfg-if",
 ]
 
 [[package]]
 name = "crossbeam-channel"
-version = "0.5.11"
+version = "0.5.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "176dc175b78f56c0f321911d9c8eb2b77a78a4860b9c19db83835fea1a46649b"
+checksum = "ab3db02a9c5b5121e1e42fbdb1aeb65f5e02624cc58c43f2884c6ccac0b82f95"
 dependencies = [
  "crossbeam-utils",
 ]
@@ -949,7 +961,7 @@ version = "0.27.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "f476fe445d41c9e991fd07515a6f463074b782242ccf4a5b7b1d1012e70824df"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "crossterm_winapi",
  "libc",
  "mio",
@@ -1005,7 +1017,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "13b588ba4ac1a99f7f2964d24b3d896ddc6bf847ee3855dbd4366f058cfcd331"
 dependencies = [
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -1069,7 +1081,7 @@ checksum = "d150dea618e920167e5973d70ae6ece4385b7164e0d799fe7c122dd0a5d912ad"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -1160,7 +1172,7 @@ checksum = "27540baf49be0d484d8f0130d7d8da3011c32a44d4fc873368154f1510e574a2"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -1189,9 +1201,9 @@ checksum = "fea41bba32d969b513997752735605054bc0dfa92b4c56bf1189f2e174be7a10"
 
 [[package]]
 name = "downcast-rs"
-version = "1.2.0"
+version = "1.2.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9ea835d29036a4087793836fa931b08837ad5e957da9e23886b29586fb9b6650"
+checksum = "75b325c5dbd37f80359721ad39aca5a29fb04c89279657cffdda8736d0c0b9d2"
 
 [[package]]
 name = "dtoa"
@@ -1228,9 +1240,9 @@ checksum = "56ce8c6da7551ec6c462cbaf3bfbc75131ebbfa1c944aeaa9dab51ca1c5f0c3b"
 
 [[package]]
 name = "dyn-clone"
-version = "1.0.16"
+version = "1.0.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "545b22097d44f8a9581187cdf93de7a71e4722bf51200cfaba810865b49a495d"
+checksum = "0d6ef0072f8a535281e4876be788938b528e9a1d43900b82c2569af7da799125"
 
 [[package]]
 name = "ego-tree"
@@ -1240,9 +1252,9 @@ checksum = "3a68a4904193147e0a8dec3314640e6db742afd5f6e634f428a6af230d9b3591"
 
 [[package]]
 name = "either"
-version = "1.9.0"
+version = "1.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a26ae43d7bcc3b814de94796a5e736d4029efb0ee900c12e2d54c993ad1a1e07"
+checksum = "11157ac094ffbdde99aa67b23417ebdd801842852b500e395a45a9c0aac03e4a"
 
 [[package]]
 name = "eml-parser"
@@ -1271,14 +1283,14 @@ dependencies = [
 
 [[package]]
 name = "enum_dispatch"
-version = "0.3.12"
+version = "0.3.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8f33313078bb8d4d05a2733a94ac4c2d8a0df9a2b84424ebf4f33bfc224a890e"
+checksum = "aa18ce2bc66555b3218614519ac839ddb759a7d6720732f979ef8d13be147ecd"
 dependencies = [
  "once_cell",
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -1299,9 +1311,9 @@ checksum = "5443807d6dff69373d433ab9ef5378ad8df50ca6298caf15de6e52e24aaf54d5"
 
 [[package]]
 name = "erased-serde"
-version = "0.4.2"
+version = "0.4.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "55d05712b2d8d88102bc9868020c9e5c7a1f5527c452b9b97450a1d006140ba7"
+checksum = "2b73807008a3c7f171cc40312f37d95ef0396e048b5848d775f54b1a4dd4a0d3"
 dependencies = [
  "serde",
 ]
@@ -1359,9 +1371,9 @@ checksum = "95765f67b4b18863968b4a1bd5bb576f732b29a4a28c7cd84c09fa3e2875f33c"
 
 [[package]]
 name = "fastrand"
-version = "2.0.1"
+version = "2.0.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "25cbce373ec4653f1a01a31e8a5e5ec0c622dc27ff9c4e6606eefef5cbbed4a5"
+checksum = "658bd65b1cf4c852a3cc96f18a8ce7b5640f6b703f905c7d74532294c2a63984"
 
 [[package]]
 name = "fd-lock"
@@ -1552,7 +1564,7 @@ checksum = "87750cf4b7a4c0625b1529e4c543c2182106e4dedc60a2a6455e00d212c489ac"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -1625,9 +1637,9 @@ dependencies = [
 
 [[package]]
 name = "getrandom"
-version = "0.2.12"
+version = "0.2.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "190092ea657667030ac6a35e305e62fc4dd69fd98ac98631e5d3a2b1575a12b5"
+checksum = "94b22e06ecb0110981051723910cbf0b5f5e09a2062dd7663334ee79a9d1286c"
 dependencies = [
  "cfg-if",
  "js-sys",
@@ -1644,11 +1656,11 @@ checksum = "4271d37baee1b8c7e4b708028c57d816cf9d2434acb33a549475f78c181f6253"
 
 [[package]]
 name = "git2"
-version = "0.18.1"
+version = "0.18.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fbf97ba92db08df386e10c8ede66a2a0369bd277090afd8710e19e38de9ec0cd"
+checksum = "232e6a7bfe35766bf715e55a88b39a700596c0ccfd88cd3680b4cdb40d66ef70"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "libc",
  "libgit2-sys",
  "log",
@@ -1690,11 +1702,11 @@ dependencies = [
 
 [[package]]
 name = "halfbrown"
-version = "0.2.4"
+version = "0.2.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5681137554ddff44396e5f149892c769d45301dd9aa19c51602a89ee214cb0ec"
+checksum = "8588661a8607108a5ca69cab034063441a0413a0b041c13618a7dd348021ef6f"
 dependencies = [
- "hashbrown 0.13.2",
+ "hashbrown 0.14.3",
  "serde",
 ]
 
@@ -1713,16 +1725,7 @@ version = "0.12.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "8a9ee70c43aaf417c914396645a0fa852624801b24ebb7ae78fe8272889ac888"
 dependencies = [
- "ahash 0.7.7",
-]
-
-[[package]]
-name = "hashbrown"
-version = "0.13.2"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "43a3c133739dddd0d2990f9a4bdf8eb4b21ef50e4851ca85ab661199821d510e"
-dependencies = [
- "ahash 0.8.7",
+ "ahash 0.7.8",
 ]
 
 [[package]]
@@ -1731,7 +1734,7 @@ version = "0.14.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "290f1a1d9242c78d09ce40a5e87e7554ee637af1351968159f4952f028f75604"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "allocator-api2",
  "rayon",
 ]
@@ -1769,9 +1772,9 @@ checksum = "2304e00983f87ffb38b55b444b5e3b60a884b5d30c0fca7d82fe33449bbe55ea"
 
 [[package]]
 name = "hermit-abi"
-version = "0.3.4"
+version = "0.3.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5d3d0e0f38255e7fa3cf31335b3a56f05febd18025f4db5ef7a0cfb4f8da651f"
+checksum = "d231dfb89cfffdbc30e7fc41579ed6066ad03abda9e567ccafae602b97ec5024"
 
 [[package]]
 name = "hex"
@@ -1804,9 +1807,9 @@ dependencies = [
 
 [[package]]
 name = "http"
-version = "0.2.11"
+version = "0.2.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8947b1a6fad4393052c7ba1f4cd97bed3e953a95c79c92ad9b051a04611d9fbb"
+checksum = "601cbb57e577e2f5ef5be8e7b83f0f63994f25aa94d673e54a92d5c516d101f1"
 dependencies = [
  "bytes",
  "fnv",
@@ -1838,9 +1841,9 @@ checksum = "df3b46402a9d5adb4c86a0cf463f42e19994e3ee891101b1841f30a545cb49a9"
 
 [[package]]
 name = "human-date-parser"
-version = "0.1.1"
+version = "0.1.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "92d65b3ad1fdc03306397b6004b4f8f765cf7467194a1080b4530eeed5a2f0bc"
+checksum = "c5cbf96a7157cc349eeafe4595e4f283c3fcab73b5a656d8b2cc00a870a74e1a"
 dependencies = [
  "chrono",
  "pest",
@@ -1915,9 +1918,9 @@ dependencies = [
 
 [[package]]
 name = "indexmap"
-version = "2.2.2"
+version = "2.2.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "824b2ae422412366ba479e8111fd301f7b5faece8149317bb81925979a53f520"
+checksum = "168fb715dda47215e360912c096649d23d58bf392ac62f73919e831745e40f26"
 dependencies = [
  "equivalent",
  "hashbrown 0.14.3",
@@ -1926,9 +1929,9 @@ dependencies = [
 
 [[package]]
 name = "indicatif"
-version = "0.17.7"
+version = "0.17.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fb28741c9db9a713d93deb3bb9515c20788cef5815265bee4980e87bde7e0f25"
+checksum = "763a5a8f45087d6bcea4222e7b72c291a054edf80e4ef6efd2a4979878c7bea3"
 dependencies = [
  "console",
  "instant",
@@ -1939,9 +1942,9 @@ dependencies = [
 
 [[package]]
 name = "indoc"
-version = "2.0.4"
+version = "2.0.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1e186cfbae8084e513daff4240b4797e342f988cecda4fb6c939150f96315fd8"
+checksum = "b248f5224d1d606005e02c97f5aa4e88eeb230488bcc03bc9ca4d7991399f2b5"
 
 [[package]]
 name = "inotify"
@@ -2029,18 +2032,18 @@ dependencies = [
 
 [[package]]
 name = "itertools"
-version = "0.12.0"
+version = "0.12.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "25db6b064527c5d482d0423354fcd07a89a2dfe07b67892e62411946db7f07b0"
+checksum = "ba291022dbbd398a455acf126c1e341954079855bc60dfdda641363bd6922569"
 dependencies = [
  "either",
 ]
 
 [[package]]
 name = "itoa"
-version = "1.0.10"
+version = "1.0.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b1a46d1a171d865aa5f83f92695765caa047a9b4cbae2cbf37dbd613a793fd4c"
+checksum = "49f1f14873335454500d59611f1cf4a4b0f786f9ac11f4312a78e4cf2566695b"
 
 [[package]]
 name = "itoap"
@@ -2050,9 +2053,9 @@ checksum = "9028f49264629065d057f340a86acb84867925865f73bbf8d47b4d149a7e88b8"
 
 [[package]]
 name = "jobserver"
-version = "0.1.27"
+version = "0.1.28"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8c37f63953c4c63420ed5fd3d6d398c719489b9f872b9fa683262f8edd363c7d"
+checksum = "ab46a6e9526ddef3ae7f787c06f0f2600639ba80ea3eade3d8e670a2230f51d6"
 dependencies = [
  "libc",
 ]
@@ -2065,9 +2068,9 @@ checksum = "72167d68f5fce3b8655487b8038691a3c9984ee769590f93f2a631f4ad64e4f5"
 
 [[package]]
 name = "js-sys"
-version = "0.3.67"
+version = "0.3.69"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9a1d36f1235bc969acba30b7f5990b864423a6068a10f7c90ae8f0112e3a59d1"
+checksum = "29c15563dc2726973df627357ce0c9ddddbea194836909d655df6a75d2cf296d"
 dependencies = [
  "wasm-bindgen",
 ]
@@ -2210,12 +2213,12 @@ dependencies = [
 
 [[package]]
 name = "libloading"
-version = "0.8.1"
+version = "0.8.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c571b676ddfc9a8c12f1f3d3085a7b163966a8fd8098a90640953ce5f6170161"
+checksum = "0c2a198fb6b0eada2a8df47933734e6d35d350665a33a3593d7164fa52c75c19"
 dependencies = [
  "cfg-if",
- "windows-sys 0.48.0",
+ "windows-targets 0.52.4",
 ]
 
 [[package]]
@@ -2236,9 +2239,9 @@ dependencies = [
 
 [[package]]
 name = "libproc"
-version = "0.14.2"
+version = "0.14.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "229004ebba9d1d5caf41623f1523b6d52abb47d9f6ab87f7e6fc992e3b854aef"
+checksum = "8eb6497078a4c9c2aca63df56d8dce6eb4381d53a960f781a3a748f7ea97436d"
 dependencies = [
  "bindgen",
  "errno",
@@ -2247,13 +2250,12 @@ dependencies = [
 
 [[package]]
 name = "libredox"
-version = "0.0.1"
+version = "0.1.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "85c833ca1e66078851dba29046874e38f08b2c883700aa29a03ddd3b23814ee8"
+checksum = "c0ff37bd590ca25063e35af745c343cb7a0271906fb7b37e4813e8f79f00268d"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "libc",
- "redox_syscall",
 ]
 
 [[package]]
@@ -2283,9 +2285,9 @@ dependencies = [
 
 [[package]]
 name = "libz-sys"
-version = "1.1.15"
+version = "1.1.16"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "037731f5d3aaa87a5675e895b63ddff1a87624bc29f77004ea829809654e48f6"
+checksum = "5e143b5e666b2695d28f6bca6497720813f699c9602dd7f5cac91008b8ada7f9"
 dependencies = [
  "cc",
  "libc",
@@ -2326,9 +2328,9 @@ checksum = "90ed8c1e510134f979dbc4f070f87d4313098b704861a105fe34231c70a3901c"
 
 [[package]]
 name = "lru"
-version = "0.12.1"
+version = "0.12.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2994eeba8ed550fd9b47a0b38f0242bc3344e496483c6180b69139cc2fa5d1d7"
+checksum = "d3262e75e648fce39813cb56ac41f3c3e3f65217ebf3844d818d1f9398cfb0dc"
 dependencies = [
  "hashbrown 0.14.3",
 ]
@@ -2356,9 +2358,9 @@ dependencies = [
 
 [[package]]
 name = "lsp-types"
-version = "0.95.0"
+version = "0.95.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "158c1911354ef73e8fe42da6b10c0484cb65c7f1007f28022e847706c1ab6984"
+checksum = "8e34d33a8e9b006cd3fc4fe69a921affa097bae4bb65f76271f4644f9a334365"
 dependencies = [
  "bitflags 1.3.2",
  "serde",
@@ -2437,9 +2439,9 @@ dependencies = [
 
 [[package]]
 name = "memchr"
-version = "2.7.1"
+version = "2.7.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "523dc4f511e55ab87b694dc30d0f820d60906ef06413f93d4d7a1385599cc149"
+checksum = "6c8640c5d730cb13ebd907d8d04b52f55ac9a2eec55b440c8892f40d56c76c1d"
 
 [[package]]
 name = "memmap2"
@@ -2478,7 +2480,7 @@ checksum = "dcf09caffaac8068c346b6df2a7fc27a177fd20b39421a39ce0a211bde679a6c"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -2514,9 +2516,9 @@ checksum = "68354c5c6bd36d73ff3feceb05efa59b6acb7626617f4962be322a825e61f79a"
 
 [[package]]
 name = "miniz_oxide"
-version = "0.7.1"
+version = "0.7.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e7810e0be55b428ada41041c41f32c9f1a42817901b4ccf45fa3d4b6561e74c7"
+checksum = "9d811f3e15f28568be3407c8e7fdb6514c1cda3cb30683f15b6a1a1dc4ea14a7"
 dependencies = [
  "adler",
 ]
@@ -2553,9 +2555,9 @@ dependencies = [
 
 [[package]]
 name = "multiversion"
-version = "0.7.3"
+version = "0.7.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b2c7b9d7fe61760ce5ea19532ead98541f6b4c495d87247aff9826445cf6872a"
+checksum = "c4851161a11d3ad0bf9402d90ffc3967bf231768bfd7aeb61755ad06dbf1a142"
 dependencies = [
  "multiversion-macros",
  "target-features",
@@ -2563,9 +2565,9 @@ dependencies = [
 
 [[package]]
 name = "multiversion-macros"
-version = "0.7.3"
+version = "0.7.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "26a83d8500ed06d68877e9de1dde76c1dbb83885dcdbda4ef44ccbc3fbda2ac8"
+checksum = "79a74ddee9e0c27d2578323c13905793e91622148f138ba29738f9dddb835e90"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -2593,9 +2595,9 @@ dependencies = [
 
 [[package]]
 name = "new_debug_unreachable"
-version = "1.0.4"
+version = "1.0.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e4a24736216ec316047a1fc4252e27dabb04218aa4a3f37c6e7ddbf1f9782b54"
+checksum = "650eef8c711430f1a879fdd01d4745a7deea475becfb90269c06775983bbf086"
 
 [[package]]
 name = "nix"
@@ -2603,7 +2605,7 @@ version = "0.28.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "ab2156c4fce2f8df6c499cc1c763e4394b7482525bf2a9701c9d79d215f519e4"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "cfg-if",
  "cfg_aliases",
  "libc",
@@ -2625,7 +2627,7 @@ version = "6.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "6205bd8bb1e454ad2e27422015fb5e4f2bcc7e08fa8f27058670d208324a4d2d"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "crossbeam-channel",
  "filetime",
  "fsevent-sys",
@@ -2786,7 +2788,7 @@ dependencies = [
  "polars-plan",
  "polars-utils",
  "serde",
- "sqlparser",
+ "sqlparser 0.39.0",
 ]
 
 [[package]]
@@ -2795,7 +2797,7 @@ version = "0.92.2"
 dependencies = [
  "fancy-regex",
  "heck 0.5.0",
- "itertools 0.12.0",
+ "itertools 0.12.1",
  "nu-ansi-term",
  "nu-cmd-base",
  "nu-cmd-lang",
@@ -2818,7 +2820,7 @@ dependencies = [
 name = "nu-cmd-lang"
 version = "0.92.2"
 dependencies = [
- "itertools 0.12.0",
+ "itertools 0.12.1",
  "nu-engine",
  "nu-parser",
  "nu-protocol",
@@ -2866,7 +2868,7 @@ dependencies = [
  "human-date-parser",
  "indexmap",
  "indicatif",
- "itertools 0.12.0",
+ "itertools 0.12.1",
  "log",
  "lscolors",
  "md-5",
@@ -2920,7 +2922,7 @@ dependencies = [
  "tabled",
  "terminal_size",
  "titlecase",
- "toml 0.8.8",
+ "toml 0.8.12",
  "trash",
  "umask",
  "unicode-segmentation",
@@ -3018,7 +3020,7 @@ version = "0.92.2"
 dependencies = [
  "bytesize",
  "chrono",
- "itertools 0.12.0",
+ "itertools 0.12.1",
  "log",
  "nu-engine",
  "nu-path",
@@ -3099,7 +3101,7 @@ dependencies = [
  "serde",
  "serde_json",
  "strum",
- "strum_macros 0.26.1",
+ "strum_macros 0.26.2",
  "thiserror",
  "typetag",
 ]
@@ -3232,6 +3234,34 @@ dependencies = [
  "semver",
 ]
 
+[[package]]
+name = "nu_plugin_polars"
+version = "0.92.2"
+dependencies = [
+ "chrono",
+ "chrono-tz",
+ "fancy-regex",
+ "indexmap",
+ "nu-cmd-lang",
+ "nu-command",
+ "nu-engine",
+ "nu-parser",
+ "nu-plugin",
+ "nu-plugin-test-support",
+ "nu-protocol",
+ "num",
+ "polars",
+ "polars-arrow",
+ "polars-io",
+ "polars-ops",
+ "polars-plan",
+ "polars-utils",
+ "serde",
+ "sqlparser 0.43.1",
+ "typetag",
+ "uuid",
+]
+
 [[package]]
 name = "nu_plugin_query"
 version = "0.92.2"
@@ -3271,13 +3301,19 @@ dependencies = [
 
 [[package]]
 name = "num-complex"
-version = "0.4.4"
+version = "0.4.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1ba157ca0885411de85d6ca030ba7e2a83a28636056c7c699b07c8b6f7383214"
+checksum = "23c6602fda94a57c990fe0df199a035d83576b496aa29f4e634a8ac6004e68a6"
 dependencies = [
  "num-traits",
 ]
 
+[[package]]
+name = "num-conv"
+version = "0.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "51d515d32fb182ee37cda2ccdcb92950d6a3c2893aa280e540671c2cd0f3b1d9"
+
 [[package]]
 name = "num-format"
 version = "0.4.4"
@@ -3290,19 +3326,18 @@ dependencies = [
 
 [[package]]
 name = "num-integer"
-version = "0.1.45"
+version = "0.1.46"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "225d3389fb3509a24c93f5c29eb6bde2586b98d9f016636dff58d7c6f7569cd9"
+checksum = "7969661fd2958a5cb096e56c8e1ad0444ac2bbcd0061bd28660485a44879858f"
 dependencies = [
- "autocfg",
  "num-traits",
 ]
 
 [[package]]
 name = "num-iter"
-version = "0.1.43"
+version = "0.1.44"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7d03e6c028c5dc5cac6e2dec0efda81fc887605bb3d884578bb6d6bf7514e252"
+checksum = "d869c01cc0c455284163fd0092f1f93835385ccab5a98a0dcc497b2f8bf055a9"
 dependencies = [
  "autocfg",
  "num-integer",
@@ -3323,9 +3358,9 @@ dependencies = [
 
 [[package]]
 name = "num-traits"
-version = "0.2.17"
+version = "0.2.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "39e3200413f237f41ab11ad6d161bc7239c84dcb631773ccd7de3dfe4b5c267c"
+checksum = "da0df0e5185db44f69b44f26786fe401b6c293d1907744beaa7fa62b2e5a517a"
 dependencies = [
  "autocfg",
  "libm",
@@ -3343,9 +3378,9 @@ dependencies = [
 
 [[package]]
 name = "num_threads"
-version = "0.1.6"
+version = "0.1.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2819ce041d2ee131036f4fc9d6ae7ae125a3a40e97ba64d04fe799ad9dabbb44"
+checksum = "5c7398b9c8b70908f6371f47ed36737907c87c52af34c268fed0bf0ceb92ead9"
 dependencies = [
  "libc",
 ]
@@ -3408,9 +3443,9 @@ checksum = "3fdb12b2476b595f9358c5161aa467c2438859caa136dec86c26fdd2efe17b92"
 
 [[package]]
 name = "open"
-version = "5.1.1"
+version = "5.1.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "68b3fbb0d52bf0cbb5225ba3d2c303aa136031d43abff98284332a9981ecddec"
+checksum = "449f0ff855d85ddbf1edd5b646d65249ead3f5e422aaa86b7d2d0b049b103e32"
 dependencies = [
  "is-wsl",
  "libc",
@@ -3419,11 +3454,11 @@ dependencies = [
 
 [[package]]
 name = "openssl"
-version = "0.10.63"
+version = "0.10.64"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "15c9d69dd87a29568d4d017cfe8ec518706046a05184e5aea92d0af890b803c8"
+checksum = "95a0481286a310808298130d22dd1fef0fa571e05a8f44ec801801e84b216b1f"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "cfg-if",
  "foreign-types",
  "libc",
@@ -3440,7 +3475,7 @@ checksum = "a948666b637a0f465e8564c73e89d4dde00d72d4d473cc972f390fc3dcee7d9c"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -3460,9 +3495,9 @@ dependencies = [
 
 [[package]]
 name = "openssl-sys"
-version = "0.9.99"
+version = "0.9.102"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "22e1bf214306098e4832460f797824c05d25aacdf896f64a985fb0fd992454ae"
+checksum = "c597637d56fbc83893a35eb0dd04b2b8e7a50c91e64e9493e398b5df4fb45fa2"
 dependencies = [
  "cc",
  "libc",
@@ -3473,9 +3508,9 @@ dependencies = [
 
 [[package]]
 name = "ordered-multimap"
-version = "0.7.1"
+version = "0.7.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a4d6a8c22fc714f0c2373e6091bf6f5e9b37b1bc0b1184874b7e0a4e303d318f"
+checksum = "49203cdcae0030493bad186b28da2fa25645fa276a51b6fec8010d281e02ef79"
 dependencies = [
  "dlv-list",
  "hashbrown 0.14.3",
@@ -3573,12 +3608,6 @@ version = "0.2.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "8835116a5c179084a830efb3adc117ab007512b535bc1a21c991d3b32a6b44dd"
 
-[[package]]
-name = "peeking_take_while"
-version = "0.1.2"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "19b17cddbe7ec3f8bc800887bab5e717348c95ea2ca0b1bf0837fb964dc67099"
-
 [[package]]
 name = "percent-encoding"
 version = "2.3.1"
@@ -3593,9 +3622,9 @@ checksum = "f658886ed52e196e850cfbbfddab9eaa7f6d90dd0929e264c31e5cec07e09e57"
 
 [[package]]
 name = "pest"
-version = "2.7.6"
+version = "2.7.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1f200d8d83c44a45b21764d1916299752ca035d15ecd46faca3e9a2a2bf6ad06"
+checksum = "311fb059dee1a7b802f036316d790138c613a4e8b180c822e3925a662e9f0c95"
 dependencies = [
  "memchr",
  "thiserror",
@@ -3604,9 +3633,9 @@ dependencies = [
 
 [[package]]
 name = "pest_derive"
-version = "2.7.6"
+version = "2.7.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bcd6ab1236bbdb3a49027e920e693192ebfe8913f6d60e294de57463a493cfde"
+checksum = "f73541b156d32197eecda1a4014d7f868fd2bcb3c550d5386087cfba442bf69c"
 dependencies = [
  "pest",
  "pest_generator",
@@ -3614,22 +3643,22 @@ dependencies = [
 
 [[package]]
 name = "pest_generator"
-version = "2.7.6"
+version = "2.7.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2a31940305ffc96863a735bef7c7994a00b325a7138fdbc5bda0f1a0476d3275"
+checksum = "c35eeed0a3fab112f75165fdc026b3913f4183133f19b49be773ac9ea966e8bd"
 dependencies = [
  "pest",
  "pest_meta",
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
 name = "pest_meta"
-version = "2.7.6"
+version = "2.7.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a7ff62f5259e53b78d1af898941cdcdccfae7385cf7d793a6e55de5d05bb4b7d"
+checksum = "2adbf29bb9776f28caece835398781ab24435585fe0d4dc1374a61db5accedca"
 dependencies = [
  "once_cell",
  "pest",
@@ -3715,7 +3744,7 @@ dependencies = [
  "phf_shared 0.11.2",
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -3738,9 +3767,9 @@ dependencies = [
 
 [[package]]
 name = "pin-project-lite"
-version = "0.2.13"
+version = "0.2.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8afb450f006bf6385ca15ef45d71d2288452bc3683ce2e2cacc0d18e4be60b58"
+checksum = "bda66fc9667c18cb2758a2ac84d1167245054bcf85d5d1aaa6923f45801bdd02"
 
 [[package]]
 name = "pin-utils"
@@ -3750,9 +3779,9 @@ checksum = "8b870d8c151b6f2fb93e84a13146138f05d02ed11c7e7c54f8826aaaf7c9f184"
 
 [[package]]
 name = "pkg-config"
-version = "0.3.29"
+version = "0.3.30"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2900ede94e305130c13ddd391e0ab7cbaeb783945ae07a279c268cb05109c6cb"
+checksum = "d231b230927b5e4ad203db57bbcbee2802f6bce620b1e4a9024a07d94e2907ec"
 
 [[package]]
 name = "planus"
@@ -3795,7 +3824,7 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "faacd21a2548fa6d50c72d6b8d4649a8e029a0f3c6c5545b7f436f0610e49b0f"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "atoi",
  "atoi_simd",
  "avro-schema",
@@ -3857,11 +3886,12 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "befd4d280a82219a01035c4f901319ceba65998c594d0c64f9a439cdee1d7777"
 dependencies = [
- "ahash 0.8.7",
- "bitflags 2.4.2",
+ "ahash 0.8.11",
+ "bitflags 2.5.0",
  "bytemuck",
  "chrono",
  "chrono-tz",
+ "comfy-table",
  "either",
  "hashbrown 0.14.3",
  "indexmap",
@@ -3903,7 +3933,7 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b51fba2cf014cb39c2b38353d601540fb9db643be65abb9ca8ff44b9c4c4a88e"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "async-trait",
  "atoi_simd",
  "bytes",
@@ -3944,7 +3974,7 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "973d1f40ba964e70cf0038779056a7850f649538f72d8828c21bc1a7bce312ed"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "chrono",
  "fallible-streaming-iterator",
  "hashbrown 0.14.3",
@@ -3965,8 +3995,8 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d83343e413346f048f3a5ad07c0ea4b5d0bada701a482878213142970b0ddff8"
 dependencies = [
- "ahash 0.8.7",
- "bitflags 2.4.2",
+ "ahash 0.8.11",
+ "bitflags 2.5.0",
  "glob",
  "once_cell",
  "polars-arrow",
@@ -3989,7 +4019,7 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "6395f5fd5e1adf016fd6403c0a493181c1a349a7a145b2687cdf50a0d630310a"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "argminmax",
  "base64 0.21.7",
  "bytemuck",
@@ -4022,7 +4052,7 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b664cac41636cc9f146fba584a8e7c2790d7335a278964529fa3e9b4eae96daf"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "async-stream",
  "base64 0.21.7",
  "brotli",
@@ -4072,7 +4102,7 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "7fb7d7527be2aa33baace9000f6772eb9df7cd57ec010a4b273435d2dc1349e8"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "bytemuck",
  "chrono-tz",
  "once_cell",
@@ -4119,7 +4149,7 @@ dependencies = [
  "rand",
  "serde",
  "serde_json",
- "sqlparser",
+ "sqlparser 0.39.0",
 ]
 
 [[package]]
@@ -4149,7 +4179,7 @@ version = "0.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "38f9c955bb1e9b55d835aeb7fe4e4e8826e01abe5f0ada979ceb7d2b9af7b569"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "bytemuck",
  "hashbrown 0.14.3",
  "indexmap",
@@ -4247,7 +4277,7 @@ version = "3.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "6d37c51ca738a55da99dc0c4a34860fd675453b8b36209178c2249bb13651284"
 dependencies = [
- "toml_edit 0.21.0",
+ "toml_edit 0.21.1",
 ]
 
 [[package]]
@@ -4275,9 +4305,9 @@ dependencies = [
 
 [[package]]
 name = "proc-macro2"
-version = "1.0.78"
+version = "1.0.79"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e2422ad645d89c99f8f3e6b88a9fdeca7fabeac836b1002371c4367c8f984aae"
+checksum = "e835ff2298f5721608eb1a980ecaee1aef2c132bf95ecc026a11b7bf3c01c02e"
 dependencies = [
  "unicode-ident",
 ]
@@ -4288,7 +4318,7 @@ version = "0.16.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "731e0d9356b0c25f16f33b5be79b1c57b562f141ebfcdb0ad8ac2c13a24293b4"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "chrono",
  "flate2",
  "hex",
@@ -4303,7 +4333,7 @@ version = "0.16.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "2d3554923a69f4ce04c4a754260c338f505ce22642d3830e049a399fc2059a29"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "chrono",
  "hex",
 ]
@@ -4460,16 +4490,16 @@ dependencies = [
 
 [[package]]
 name = "ratatui"
-version = "0.26.0"
+version = "0.26.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "154b85ef15a5d1719bcaa193c3c81fe645cd120c156874cd660fe49fd21d1373"
+checksum = "bcb12f8fbf6c62614b0d56eb352af54f6a22410c3b079eb53ee93c7b97dd31d8"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "cassowary",
  "compact_str",
  "crossterm",
  "indoc",
- "itertools 0.12.0",
+ "itertools 0.12.1",
  "lru",
  "paste",
  "stability",
@@ -4509,9 +4539,9 @@ dependencies = [
 
 [[package]]
 name = "redox_users"
-version = "0.4.4"
+version = "0.4.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a18479200779601e498ada4e8c1e1f50e3ee19deb0259c25825a98b5603b2cb4"
+checksum = "bd283d9651eeda4b2a83a43c1c91b266c40fd76ecd39a50a8c630ae69dc72891"
 dependencies = [
  "getrandom",
  "libredox",
@@ -4528,14 +4558,14 @@ dependencies = [
  "chrono",
  "crossterm",
  "fd-lock",
- "itertools 0.12.0",
+ "itertools 0.12.1",
  "nu-ansi-term",
  "rusqlite",
  "serde",
  "serde_json",
  "strip-ansi-escapes",
  "strum",
- "strum_macros 0.26.1",
+ "strum_macros 0.26.2",
  "thiserror",
  "unicode-segmentation",
  "unicode-width",
@@ -4558,14 +4588,14 @@ checksum = "5fddb4f8d99b0a2ebafc65a87a69a7b9875e4b1ae1f00db265d300ef7f28bccc"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
 name = "regex"
-version = "1.10.3"
+version = "1.10.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b62dbe01f0b06f9d8dc7d49e05a0785f153b00b2c227856282f671e0318c9b15"
+checksum = "c117dbdfde9c8308975b6a18d71f3f385c89461f7b3fb054288ecf2a2058ba4c"
 dependencies = [
  "aho-corasick",
  "memchr",
@@ -4575,9 +4605,9 @@ dependencies = [
 
 [[package]]
 name = "regex-automata"
-version = "0.4.5"
+version = "0.4.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5bb987efffd3c6d0d8f5f89510bb458559eab11e4f869acb20bf845e016259cd"
+checksum = "86b83b8b9847f9bf95ef68afb0b8e6cdb80f498442f5179a29fad448fcc1eaea"
 dependencies = [
  "aho-corasick",
  "memchr",
@@ -4592,9 +4622,9 @@ checksum = "30b661b2f27137bdbc16f00eda72866a92bb28af1753ffbd56744fb6e2e9cd8e"
 
 [[package]]
 name = "regex-syntax"
-version = "0.8.2"
+version = "0.8.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c08c74e62047bb2de4ff487b251e4a92e24f48745648451635cec7d591162d9f"
+checksum = "adad44e29e4c806119491a7f06f03de4d1af22c3a680dd47f1e6e179439d1f56"
 
 [[package]]
 name = "relative-path"
@@ -4604,18 +4634,18 @@ checksum = "e898588f33fdd5b9420719948f9f2a32c922a246964576f71ba7f24f80610fbc"
 
 [[package]]
 name = "rend"
-version = "0.4.1"
+version = "0.4.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a2571463863a6bd50c32f94402933f03457a3fbaf697a707c5be741e459f08fd"
+checksum = "71fe3824f5629716b1589be05dacd749f6aa084c87e00e016714a8cdfccc997c"
 dependencies = [
  "bytecheck",
 ]
 
 [[package]]
 name = "rfc2047-decoder"
-version = "1.0.2"
+version = "1.0.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9e372613f15fc5171f9052b0c1fbafca5b1e5b0ba86aa13c9c39fd91ca1f7955"
+checksum = "e90a668c463c412c3118ae1883e18b53d812c349f5af7a06de3ba4bb0c17cc73"
 dependencies = [
  "base64 0.21.7",
  "charset",
@@ -4627,9 +4657,9 @@ dependencies = [
 
 [[package]]
 name = "rkyv"
-version = "0.7.43"
+version = "0.7.44"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "527a97cdfef66f65998b5f3b637c26f5a5ec09cc52a3f9932313ac645f4190f5"
+checksum = "5cba464629b3394fc4dbc6f940ff8f5b4ff5c7aef40f29166fd4ad12acbc99c0"
 dependencies = [
  "bitvec",
  "bytecheck",
@@ -4645,9 +4675,9 @@ dependencies = [
 
 [[package]]
 name = "rkyv_derive"
-version = "0.7.43"
+version = "0.7.44"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b5c462a1328c8e67e4d6dbad1eb0355dd43e8ab432c6e227a43657f16ade5033"
+checksum = "a7dddfff8de25e6f62b9d64e6e432bf1c6736c57d20323e15ee10435fbda7c65"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -4721,7 +4751,7 @@ dependencies = [
  "regex",
  "relative-path",
  "rustc_version",
- "syn 2.0.48",
+ "syn 2.0.58",
  "unicode-ident",
 ]
 
@@ -4731,7 +4761,7 @@ version = "0.31.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b838eba278d213a8beaf485bd313fd580ca4505a00d5871caeb1457c55322cae"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "chrono",
  "fallible-iterator",
  "fallible-streaming-iterator",
@@ -4760,7 +4790,7 @@ dependencies = [
  "proc-macro2",
  "quote",
  "rust-embed-utils",
- "syn 2.0.48",
+ "syn 2.0.58",
  "walkdir",
 ]
 
@@ -4786,9 +4816,9 @@ dependencies = [
 
 [[package]]
 name = "rust_decimal"
-version = "1.33.1"
+version = "1.35.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "06676aec5ccb8fc1da723cc8c0f9a46549f21ebb8753d3915c6c41db1e7f1dc4"
+checksum = "1790d1c4c0ca81211399e0e0af16333276f375209e71a37b67698a373db5b47a"
 dependencies = [
  "arrayvec 0.7.4",
  "borsh",
@@ -4823,11 +4853,11 @@ dependencies = [
 
 [[package]]
 name = "rustix"
-version = "0.38.31"
+version = "0.38.32"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6ea3e1a662af26cd7a3ba09c0297a31af215563ecf42817c98df621387f4e949"
+checksum = "65e04861e65f21776e67888bfbea442b3642beaa0138fdb1dd7a84a52dffdb89"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "errno",
  "libc",
  "linux-raw-sys",
@@ -4836,15 +4866,15 @@ dependencies = [
 
 [[package]]
 name = "rustversion"
-version = "1.0.14"
+version = "1.0.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7ffc183a10b4478d04cbbbfc96d0873219d962dd5accaff2ffbd4ceb7df837f4"
+checksum = "80af6f9131f277a45a3fba6ce8e2258037bb0477a67e610d3c1fe046ab31de47"
 
 [[package]]
 name = "ryu"
-version = "1.0.16"
+version = "1.0.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f98d2aa92eebf49b69786be48e4477826b256916e84a57ff2a4f21923b48eb4c"
+checksum = "e86697c916019a8588c99b5fac3cead74ec0b4b819707a682fd4d23fa0ce1ba1"
 
 [[package]]
 name = "same-file"
@@ -4882,7 +4912,7 @@ version = "0.19.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "5b80b33679ff7a0ea53d37f3b39de77ea0c75b12c5805ac43ec0c33b3051af1b"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "cssparser",
  "ego-tree",
  "html5ever",
@@ -4899,9 +4929,9 @@ checksum = "1c107b6f4780854c8b126e228ea8869f4d7b71260f962fefb57b996b8959ba6b"
 
 [[package]]
 name = "security-framework"
-version = "2.9.2"
+version = "2.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "05b64fb303737d99b81884b2c63433e9ae28abebe5eb5045dcdd175dc2ecf4de"
+checksum = "770452e37cad93e0a50d5abc3990d2bc351c36d0328f86cefec2f2fb206eaef6"
 dependencies = [
  "bitflags 1.3.2",
  "core-foundation",
@@ -4912,9 +4942,9 @@ dependencies = [
 
 [[package]]
 name = "security-framework-sys"
-version = "2.9.1"
+version = "2.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e932934257d3b408ed8f30db49d85ea163bfe74961f017f405b025af298f0c7a"
+checksum = "41f3cc463c0ef97e11c3461a9d3787412d30e8e7eb907c79180c4a57bf7c04ef"
 dependencies = [
  "core-foundation-sys",
  "libc",
@@ -4926,7 +4956,7 @@ version = "0.25.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "4eb30575f3638fc8f6815f448d50cb1a2e255b0897985c8c59f4d37b72a07b06"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "cssparser",
  "derive_more",
  "fxhash",
@@ -4941,9 +4971,9 @@ dependencies = [
 
 [[package]]
 name = "semver"
-version = "1.0.21"
+version = "1.0.22"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b97ed7a9823b74f99c7742f5336af7be5ecd3eeafcb1507d1fa93347b1d589b0"
+checksum = "92d43fe69e652f3df9bdc2b85b2854a0825b86e4fb76bc44d945137d053639ca"
 
 [[package]]
 name = "seq-macro"
@@ -4953,29 +4983,29 @@ checksum = "a3f0bf26fd526d2a95683cd0f87bf103b8539e2ca1ef48ce002d67aad59aa0b4"
 
 [[package]]
 name = "serde"
-version = "1.0.196"
+version = "1.0.197"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "870026e60fa08c69f064aa766c10f10b1d62db9ccd4d0abb206472bee0ce3b32"
+checksum = "3fb1c873e1b9b056a4dc4c0c198b24c3ffa059243875552b2bd0933b1aee4ce2"
 dependencies = [
  "serde_derive",
 ]
 
 [[package]]
 name = "serde_derive"
-version = "1.0.196"
+version = "1.0.197"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "33c85360c95e7d137454dc81d9a4ed2b8efd8fbe19cee57357b32b9771fccb67"
+checksum = "7eb0b34b42edc17f6b7cac84a52a1c5f0e1bb2227e997ca9011ea3dd34e8610b"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
 name = "serde_json"
-version = "1.0.114"
+version = "1.0.115"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c5f09b1bd632ef549eaa9f60a1f8de742bdbc698e6cee2095fc84dde5f549ae0"
+checksum = "12dc5c46daa8e9fdf4f5e71b6cf9a53f2487da0e86e55808e2d35539666497dd"
 dependencies = [
  "indexmap",
  "itoa",
@@ -4985,13 +5015,13 @@ dependencies = [
 
 [[package]]
 name = "serde_repr"
-version = "0.1.18"
+version = "0.1.19"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0b2e6b945e9d3df726b65d6ee24060aff8e3533d431f677a9695db04eff9dfdb"
+checksum = "6c64451ba24fc7a6a2d60fc75dd9c83c90903b19028d4eff35e88fc1e86564e9"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -5017,9 +5047,9 @@ dependencies = [
 
 [[package]]
 name = "serde_yaml"
-version = "0.9.30"
+version = "0.9.34+deprecated"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b1bf28c79a99f70ee1f1d83d10c875d2e70618417fda01ad1785e027579d9d38"
+checksum = "6a8b1a1a2ebf674015cc02edccce75287f1a0130d394307b36743c2f5d504b47"
 dependencies = [
  "indexmap",
  "itoa",
@@ -5050,7 +5080,7 @@ checksum = "b93fb4adc70021ac1b47f7d45e8cc4169baaa7ea58483bc5b721d19a26202212"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -5128,11 +5158,11 @@ dependencies = [
 
 [[package]]
 name = "simd-json"
-version = "0.13.8"
+version = "0.13.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2faf8f101b9bc484337a6a6b0409cf76c139f2fb70a9e3aee6b6774be7bfbf76"
+checksum = "b0b84c23a1066e1d650ebc99aa8fb9f8ed0ab96fd36e2e836173c92fc9fb29bc"
 dependencies = [
- "ahash 0.8.7",
+ "ahash 0.8.11",
  "getrandom",
  "halfbrown",
  "lexical-core",
@@ -5158,9 +5188,9 @@ checksum = "fa42c91313f1d05da9b26f267f931cf178d4aba455b4c4622dd7355eb80c6640"
 
 [[package]]
 name = "simplelog"
-version = "0.12.1"
+version = "0.12.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "acee08041c5de3d5048c8b3f6f13fafb3026b24ba43c6a695a0c76179b844369"
+checksum = "16257adbfaef1ee58b1363bdc0664c9b8e1e30aed86049635fb5f147d065a9c0"
 dependencies = [
  "log",
  "termcolor",
@@ -5184,9 +5214,9 @@ dependencies = [
 
 [[package]]
 name = "smallvec"
-version = "1.13.1"
+version = "1.13.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e6ecd384b10a64542d77071bd64bd7b231f4ed5940fba55e98c3de13824cf3d7"
+checksum = "3c5e1a9a646d36c3599cd173a41282daf47c44583ad367b8e6837255952e5c67"
 
 [[package]]
 name = "smartstring"
@@ -5214,12 +5244,12 @@ checksum = "1b6b67fb9a61334225b5b790716f609cd58395f895b3fe8b328786812a40bc3b"
 
 [[package]]
 name = "socket2"
-version = "0.5.5"
+version = "0.5.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7b5fac59a5cb5dd637972e5fca70daf0523c9067fcdc4842f053dae04a18f8e9"
+checksum = "05ffd9c0a93b7543e062e759284fcf5f5e3b098501104bfbdde4d404db792871"
 dependencies = [
  "libc",
- "windows-sys 0.48.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
@@ -5231,6 +5261,15 @@ dependencies = [
  "log",
 ]
 
+[[package]]
+name = "sqlparser"
+version = "0.43.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f95c4bae5aba7cd30bd506f7140026ade63cff5afd778af8854026f9606bf5d4"
+dependencies = [
+ "log",
+]
+
 [[package]]
 name = "stability"
 version = "0.1.1"
@@ -5330,17 +5369,17 @@ dependencies = [
 
 [[package]]
 name = "strsim"
-version = "0.10.0"
+version = "0.11.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "73473c0e59e6d5812c5dfe2a064a6444949f089e20eec9a2e5506596494e4623"
+checksum = "7da8b5736845d9f2fcb837ea5d9e2628564b3b043a70948a3f0b778838c5fb4f"
 
 [[package]]
 name = "strum"
-version = "0.26.1"
+version = "0.26.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "723b93e8addf9aa965ebe2d11da6d7540fa2283fcea14b3371ff055f7ba13f5f"
+checksum = "5d8cec3501a5194c432b2b7976db6b7d10ec95c253208b45f83f7136aa985e29"
 dependencies = [
- "strum_macros 0.26.1",
+ "strum_macros 0.26.2",
 ]
 
 [[package]]
@@ -5353,20 +5392,20 @@ dependencies = [
  "proc-macro2",
  "quote",
  "rustversion",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
 name = "strum_macros"
-version = "0.26.1"
+version = "0.26.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7a3417fc93d76740d974a01654a09777cb500428cc874ca9f45edfe0c4d4cd18"
+checksum = "c6cf59daf282c0a494ba14fd21610a0325f9f90ec9d1231dea26bcb1d696c946"
 dependencies = [
  "heck 0.4.1",
  "proc-macro2",
  "quote",
  "rustversion",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -5424,9 +5463,9 @@ dependencies = [
 
 [[package]]
 name = "syn"
-version = "2.0.48"
+version = "2.0.58"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0f3531638e407dfc0814761abb7c00a5b54992b849452a0646b7f65c9f770f3f"
+checksum = "44cfb93f38070beee36b3fef7d4f5a16f27751d94b187b666a5cc5e9b0d30687"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -5442,7 +5481,7 @@ dependencies = [
  "proc-macro-error",
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -5456,9 +5495,9 @@ dependencies = [
 
 [[package]]
 name = "sysinfo"
-version = "0.30.5"
+version = "0.30.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1fb4f3438c8f6389c864e61221cbc97e9bca98b4daf39a5beb7bea660f528bb2"
+checksum = "e9a84fe4cfc513b41cb2596b624e561ec9e7e1c4b46328e496ed56a53514ef2a"
 dependencies = [
  "cfg-if",
  "core-foundation-sys",
@@ -5489,9 +5528,9 @@ checksum = "55937e1799185b12863d447f42597ed69d9928686b8d88a1df17376a097d8369"
 
 [[package]]
 name = "target-features"
-version = "0.1.5"
+version = "0.1.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cfb5fa503293557c5158bd215fdc225695e567a77e453f5d4452a50a193969bd"
+checksum = "c1bbb9f3c5c463a01705937a24fdabc5047929ac764b2d5b9cf681c1f5041ed5"
 
 [[package]]
 name = "tempfile"
@@ -5518,9 +5557,9 @@ dependencies = [
 
 [[package]]
 name = "termcolor"
-version = "1.1.3"
+version = "1.4.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bab24d30b911b2376f3a13cc2cd443142f0c81dda04c118693e35b3835757755"
+checksum = "06794f8f6c5c898b3275aebefa6b8a1cb24cd2c6c79397ab15774837a0bc5755"
 dependencies = [
  "winapi-util",
 ]
@@ -5543,9 +5582,9 @@ checksum = "3369f5ac52d5eb6ab48c6b4ffdc8efbcad6b89c765749064ba298f2c68a16a76"
 
 [[package]]
 name = "textwrap"
-version = "0.16.0"
+version = "0.16.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "222a222a5bfe1bba4a77b45ec488a741b3cb8872e5e499451fd7d0129c9c7c3d"
+checksum = "23d434d3f8967a09480fb04132ebe0a3e088c173e6d0ee7897abbdf4eab0f8b9"
 dependencies = [
  "smawk",
  "unicode-linebreak",
@@ -5554,29 +5593,29 @@ dependencies = [
 
 [[package]]
 name = "thiserror"
-version = "1.0.56"
+version = "1.0.58"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d54378c645627613241d077a3a79db965db602882668f9136ac42af9ecb730ad"
+checksum = "03468839009160513471e86a034bb2c5c0e4baae3b43f79ffc55c4a5427b3297"
 dependencies = [
  "thiserror-impl",
 ]
 
 [[package]]
 name = "thiserror-impl"
-version = "1.0.56"
+version = "1.0.58"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fa0faa943b50f3db30a20aa7e265dbc66076993efed8463e8de414e5d06d3471"
+checksum = "c61f3ba182994efc43764a46c018c347bc492c79f024e705f46567b418f6d4f7"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
 name = "thread_local"
-version = "1.1.7"
+version = "1.1.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3fdd6f064ccff2d6567adcb3873ca630700f00b5ad3f060c25b5dcfd9a4ce152"
+checksum = "8b9ef9bad013ada3808854ceac7b46812a6465ba368859a37e2100283d2d719c"
 dependencies = [
  "cfg-if",
  "once_cell",
@@ -5584,13 +5623,14 @@ dependencies = [
 
 [[package]]
 name = "time"
-version = "0.3.31"
+version = "0.3.34"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f657ba42c3f86e7680e53c8cd3af8abbe56b5491790b46e22e19c0d57463583e"
+checksum = "c8248b6521bb14bc45b4067159b9b6ad792e2d6d754d6c41fb50e29fefe38749"
 dependencies = [
  "deranged",
  "itoa",
  "libc",
+ "num-conv",
  "num_threads",
  "powerfmt",
  "serde",
@@ -5606,10 +5646,11 @@ checksum = "ef927ca75afb808a4d64dd374f00a2adf8d0fcff8e7b184af886c3c87ec4a3f3"
 
 [[package]]
 name = "time-macros"
-version = "0.2.16"
+version = "0.2.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "26197e33420244aeb70c3e8c78376ca46571bc4e701e4791c2cd9f57dcb3a43f"
+checksum = "7ba3a3ef41e6672a2f0f001392bb5dcd3ff0a9992d618ca761a11c3121547774"
 dependencies = [
+ "num-conv",
  "time-core",
 ]
 
@@ -5650,9 +5691,9 @@ dependencies = [
 
 [[package]]
 name = "tokio"
-version = "1.35.1"
+version = "1.37.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c89b4efa943be685f629b149f53829423f8f5531ea21249408e8e2f8671ec104"
+checksum = "1adbebffeca75fcfd058afa480fb6c0b81e165a0323f9c9d39c9697e37c46787"
 dependencies = [
  "backtrace",
  "bytes",
@@ -5693,14 +5734,14 @@ dependencies = [
 
 [[package]]
 name = "toml"
-version = "0.8.8"
+version = "0.8.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a1a195ec8c9da26928f773888e0742ca3ca1040c6cd859c919c9f59c1954ab35"
+checksum = "e9dd1545e8208b4a5af1aa9bbd0b4cf7e9ea08fabc5d0a5c67fcaafa17433aa3"
 dependencies = [
  "serde",
  "serde_spanned",
  "toml_datetime",
- "toml_edit 0.21.0",
+ "toml_edit 0.22.9",
 ]
 
 [[package]]
@@ -5722,20 +5763,31 @@ dependencies = [
  "serde",
  "serde_spanned",
  "toml_datetime",
- "winnow",
+ "winnow 0.5.40",
 ]
 
 [[package]]
 name = "toml_edit"
-version = "0.21.0"
+version = "0.21.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d34d383cd00a163b4a5b85053df514d45bc330f6de7737edfe0a93311d1eaa03"
+checksum = "6a8534fd7f78b5405e860340ad6575217ce99f38d4d5c8f2442cb5ecb50090e1"
+dependencies = [
+ "indexmap",
+ "toml_datetime",
+ "winnow 0.5.40",
+]
+
+[[package]]
+name = "toml_edit"
+version = "0.22.9"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "8e40bb779c5187258fd7aad0eb68cb8706a0a81fa712fbea808ab43c4b8374c4"
 dependencies = [
  "indexmap",
  "serde",
  "serde_spanned",
  "toml_datetime",
- "winnow",
+ "winnow 0.6.5",
 ]
 
 [[package]]
@@ -5781,13 +5833,13 @@ dependencies = [
 
 [[package]]
 name = "tree_magic_mini"
-version = "3.0.3"
+version = "3.1.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "91adfd0607cacf6e4babdb870e9bec4037c1c4b151cfd279ccefc5e0c7feaa6d"
+checksum = "77ee137597cdb361b55a4746983e4ac1b35ab6024396a419944ad473bb915265"
 dependencies = [
- "bytecount",
  "fnv",
- "lazy_static",
+ "home",
+ "memchr",
  "nom",
  "once_cell",
  "petgraph",
@@ -5813,9 +5865,9 @@ checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"
 
 [[package]]
 name = "typetag"
-version = "0.2.15"
+version = "0.2.16"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c43148481c7b66502c48f35b8eef38b6ccdc7a9f04bd4cc294226d901ccc9bc7"
+checksum = "661d18414ec032a49ece2d56eee03636e43c4e8d577047ab334c0ba892e29aaf"
 dependencies = [
  "erased-serde",
  "inventory",
@@ -5826,13 +5878,13 @@ dependencies = [
 
 [[package]]
 name = "typetag-impl"
-version = "0.2.15"
+version = "0.2.16"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "291db8a81af4840c10d636e047cac67664e343be44e24dfdbd1492df9a5d3390"
+checksum = "ac73887f47b9312552aa90ef477927ff014d63d1920ca8037c6c1951eab64bb1"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -5879,18 +5931,18 @@ checksum = "3b09c83c3c29d37506a3e260c08c03743a6bb66a9cd432c6934ab501a190571f"
 
 [[package]]
 name = "unicode-normalization"
-version = "0.1.22"
+version = "0.1.23"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5c5713f0fc4b5db668a2ac63cdb7bb4469d8c9fed047b1d0292cc7b0ce2ba921"
+checksum = "a56d1686db2308d901306f92a263857ef59ea39678a5458e7cb17f01415101f5"
 dependencies = [
  "tinyvec",
 ]
 
 [[package]]
 name = "unicode-reverse"
-version = "1.0.8"
+version = "1.0.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0bea5dacebb0d2d0a69a6700a05b59b3908bf801bf563a49bd27a1b60122962c"
+checksum = "4b6f4888ebc23094adfb574fdca9fdc891826287a6397d2cd28802ffd6f20c76"
 dependencies = [
  "unicode-segmentation",
 ]
@@ -5915,15 +5967,15 @@ checksum = "f962df74c8c05a667b5ee8bcf162993134c104e96440b663c8daa176dc772d8c"
 
 [[package]]
 name = "unsafe-libyaml"
-version = "0.2.10"
+version = "0.2.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ab4c90930b95a82d00dc9e9ac071b4991924390d46cbd0dfe566148667605e4b"
+checksum = "673aac59facbab8a9007c7f6108d11f63b603f7cabff99fabf650fea5c32b861"
 
 [[package]]
 name = "ureq"
-version = "2.9.1"
+version = "2.9.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f8cdd25c339e200129fe4de81451814e5228c9b771d57378817d6117cc2b3f97"
+checksum = "11f214ce18d8b2cbe84ed3aa6486ed3f5b285cf8d8fbdbce9f3f767a724adc35"
 dependencies = [
  "base64 0.21.7",
  "encoding_rs",
@@ -6062,9 +6114,9 @@ dependencies = [
 
 [[package]]
 name = "uucore_procs"
-version = "0.0.24"
+version = "0.0.25"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3eb9aeeb06d1f15c5b3b51acddddf3436e3e1480902b2a200618ca5dbb24e392"
+checksum = "f7f51594832e53b11811446b1cd3567722e2906a589a5b19622c5c4720977309"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -6073,9 +6125,9 @@ dependencies = [
 
 [[package]]
 name = "uuhelp_parser"
-version = "0.0.24"
+version = "0.0.25"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d841f8408028085ca65896cdd60b9925d4e407cb69989a64889f2bebbb51147b"
+checksum = "ac7a6832a5add86204d5a8d0ef41c5a11e3ddf61c0f1a508f69e7e3e1bf04e3f"
 
 [[package]]
 name = "uuid"
@@ -6084,6 +6136,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "a183cf7feeba97b4dd1c0d46788634f6221d87fa961b305bed08c851829efcc0"
 dependencies = [
  "getrandom",
+ "serde",
 ]
 
 [[package]]
@@ -6183,9 +6236,9 @@ checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"
 
 [[package]]
 name = "wasm-bindgen"
-version = "0.2.90"
+version = "0.2.92"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b1223296a201415c7fad14792dbefaace9bd52b62d33453ade1c5b5f07555406"
+checksum = "4be2531df63900aeb2bca0daaaddec08491ee64ceecbee5076636a3b026795a8"
 dependencies = [
  "cfg-if",
  "wasm-bindgen-macro",
@@ -6193,24 +6246,24 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen-backend"
-version = "0.2.90"
+version = "0.2.92"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fcdc935b63408d58a32f8cc9738a0bffd8f05cc7c002086c6ef20b7312ad9dcd"
+checksum = "614d787b966d3989fa7bb98a654e369c762374fd3213d212cfc0251257e747da"
 dependencies = [
  "bumpalo",
  "log",
  "once_cell",
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
  "wasm-bindgen-shared",
 ]
 
 [[package]]
 name = "wasm-bindgen-macro"
-version = "0.2.90"
+version = "0.2.92"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3e4c238561b2d428924c49815533a8b9121c664599558a5d9ec51f8a1740a999"
+checksum = "a1f8823de937b71b9460c0c34e25f3da88250760bec0ebac694b49997550d726"
 dependencies = [
  "quote",
  "wasm-bindgen-macro-support",
@@ -6218,22 +6271,22 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen-macro-support"
-version = "0.2.90"
+version = "0.2.92"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bae1abb6806dc1ad9e560ed242107c0f6c84335f1749dd4e8ddb012ebd5e25a7"
+checksum = "e94f17b526d0a461a191c78ea52bbce64071ed5c04c9ffe424dcb38f74171bb7"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
  "wasm-bindgen-backend",
  "wasm-bindgen-shared",
 ]
 
 [[package]]
 name = "wasm-bindgen-shared"
-version = "0.2.90"
+version = "0.2.92"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4d91413b1c31d7539ba5ef2451af3f0b833a005eb27a631cec32bc0635a8602b"
+checksum = "af190c94f2773fdb3729c55b007a722abb5384da03bc0986df4c289bf5567e96"
 
 [[package]]
 name = "wax"
@@ -6270,7 +6323,7 @@ version = "0.31.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "82fb96ee935c2cea6668ccb470fb7771f6215d1691746c2d896b447a00ad3f1f"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "rustix",
  "wayland-backend",
  "wayland-scanner",
@@ -6282,7 +6335,7 @@ version = "0.31.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "8f81f365b8b4a97f422ac0e8737c438024b5951734506b0e1d775c73030561f4"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "wayland-backend",
  "wayland-client",
  "wayland-scanner",
@@ -6294,7 +6347,7 @@ version = "0.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "ad1f61b76b6c2d8742e10f9ba5c3737f6530b4c243132c2a2ccc8aa96fe25cd6"
 dependencies = [
- "bitflags 2.4.2",
+ "bitflags 2.5.0",
  "wayland-backend",
  "wayland-client",
  "wayland-protocols",
@@ -6325,15 +6378,14 @@ dependencies = [
 
 [[package]]
 name = "which"
-version = "6.0.0"
+version = "6.0.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7fa5e0c10bf77f44aac573e498d1a82d5fbd5e91f6fc0a99e7be4b38e85e101c"
+checksum = "8211e4f58a2b2805adfbefbc07bab82958fc91e3836339b1ab7ae32465dce0d7"
 dependencies = [
  "either",
  "home",
- "once_cell",
  "rustix",
- "windows-sys 0.52.0",
+ "winsafe",
 ]
 
 [[package]]
@@ -6624,9 +6676,18 @@ checksum = "32b752e52a2da0ddfbdbcc6fceadfeede4c939ed16d13e648833a61dfb611ed8"
 
 [[package]]
 name = "winnow"
-version = "0.5.35"
+version = "0.5.40"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1931d78a9c73861da0134f453bb1f790ce49b2e30eba8410b4b79bac72b46a2d"
+checksum = "f593a95398737aeed53e489c785df13f3618e41dbcd6718c6addbf1395aa6876"
+dependencies = [
+ "memchr",
+]
+
+[[package]]
+name = "winnow"
+version = "0.6.5"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "dffa400e67ed5a4dd237983829e66475f0a4a26938c4b04c21baede6262215b8"
 dependencies = [
  "memchr",
 ]
@@ -6651,6 +6712,12 @@ dependencies = [
  "version_check",
 ]
 
+[[package]]
+name = "winsafe"
+version = "0.0.19"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d135d17ab770252ad95e9a872d365cf3090e3be864a34ab46f48555993efc904"
+
 [[package]]
 name = "wl-clipboard-rs"
 version = "0.8.1"
@@ -6710,9 +6777,9 @@ dependencies = [
 
 [[package]]
 name = "xxhash-rust"
-version = "0.8.8"
+version = "0.8.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "53be06678ed9e83edb1745eb72efc0bbcd7b5c3c35711a860906aed827a13d61"
+checksum = "927da81e25be1e1a2901d59b81b37dd2efd1fc9c9345a55007f09bf5a2d3ee03"
 
 [[package]]
 name = "yansi"
@@ -6737,7 +6804,7 @@ checksum = "9ce1b18ccd8e73a9321186f97e46f9f04b778851177567b1975109d26a08d2a6"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.48",
+ "syn 2.0.58",
 ]
 
 [[package]]
@@ -6754,27 +6821,27 @@ dependencies = [
 
 [[package]]
 name = "zstd"
-version = "0.13.0"
+version = "0.13.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bffb3309596d527cfcba7dfc6ed6052f1d39dfbd7c867aa2e865e4a449c10110"
+checksum = "2d789b1514203a1120ad2429eae43a7bd32b90976a7bb8a05f7ec02fa88cc23a"
 dependencies = [
  "zstd-safe",
 ]
 
 [[package]]
 name = "zstd-safe"
-version = "7.0.0"
+version = "7.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "43747c7422e2924c11144d5229878b98180ef8b06cca4ab5af37afc8a8d8ea3e"
+checksum = "1cd99b45c6bc03a018c8b8a86025678c87e55526064e38f9df301989dce7ec0a"
 dependencies = [
  "zstd-sys",
 ]
 
 [[package]]
 name = "zstd-sys"
-version = "2.0.9+zstd.1.5.5"
+version = "2.0.10+zstd.1.5.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9e16efa8a874a0481a574084d34cc26fdb3b99627480f785888deb6386506656"
+checksum = "c253a4914af5bafc8fa8c86ee400827e83cf6ec01195ec1f1ed8441bf00d65aa"
 dependencies = [
  "cc",
  "pkg-config",
diff --git a/Cargo.toml b/Cargo.toml
index 0b9be56a57..2708d1cf31 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -47,6 +47,7 @@ members = [
   "crates/nu_plugin_query",
   "crates/nu_plugin_custom_values",
   "crates/nu_plugin_formats",
+  "crates/nu_plugin_polars",
   "crates/nu-std",
   "crates/nu-table",
   "crates/nu-term-grid",
diff --git a/crates/nu-cmd-dataframe/src/dataframe/lazy/to_lazy.rs b/crates/nu-cmd-dataframe/src/dataframe/lazy/to_lazy.rs
index cad516b9eb..1c711cdd57 100644
--- a/crates/nu-cmd-dataframe/src/dataframe/lazy/to_lazy.rs
+++ b/crates/nu-cmd-dataframe/src/dataframe/lazy/to_lazy.rs
@@ -48,7 +48,6 @@ impl Command for ToLazyFrame {
         let df = NuDataFrame::try_from_iter(input.into_iter(), maybe_schema)?;
         let lazy = NuLazyFrame::from_dataframe(df);
         let value = Value::custom(Box::new(lazy), call.head);
-
         Ok(PipelineData::Value(value, None))
     }
 }
diff --git a/crates/nu_plugin_polars/Cargo.toml b/crates/nu_plugin_polars/Cargo.toml
new file mode 100644
index 0000000000..9a18a3650f
--- /dev/null
+++ b/crates/nu_plugin_polars/Cargo.toml
@@ -0,0 +1,78 @@
+[package]
+authors = ["The Nushell Project Developers"]
+description = "Nushell dataframe plugin commands based on polars."
+edition = "2021"
+license = "MIT"
+name = "nu_plugin_polars"
+repository = "https://github.com/nushell/nushell/tree/main/crates/nu-cmd-dataframe"
+version = "0.92.2"
+
+# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
+
+[[bin]]
+name = "nu_plugin_polars"
+bench = false
+
+[lib]
+bench = false
+
+[dependencies]
+nu-protocol = { path = "../nu-protocol", version = "0.92.2" }
+nu-plugin = { path = "../nu-plugin", version = "0.92.2" }
+
+# Potential dependencies for extras
+chrono = { workspace = true, features = ["std", "unstable-locales"], default-features = false }
+chrono-tz = "0.8"
+fancy-regex = { workspace = true }
+indexmap = { version = "2.2" }
+num = {version = "0.4"}
+serde = { version = "1.0", features = ["derive"] }
+sqlparser = { version = "0.43"}
+polars-io = { version = "0.37", features = ["avro"]}
+polars-arrow = { version = "0.37"}
+polars-ops = { version = "0.37"}
+polars-plan = { version = "0.37", features = ["regex"]}
+polars-utils = { version = "0.37"}
+typetag = "0.2"
+uuid = { version = "1.7", features = ["v4", "serde"] }
+
+[dependencies.polars]
+features = [
+	"arg_where",
+	"checked_arithmetic",
+	"concat_str",
+	"cross_join",
+	"csv",
+	"cum_agg",
+	"default",
+	"dtype-categorical",
+	"dtype-datetime",
+	"dtype-struct",
+	"dtype-i8",
+	"dtype-i16",
+	"dtype-u8",
+	"dtype-u16",
+	"dynamic_group_by",
+	"ipc",
+	"is_in",
+	"json",
+	"lazy",
+	"object",
+	"parquet",
+	"random",
+	"rolling_window",
+	"rows",
+	"serde",
+	"serde-lazy",
+	"strings",
+	"to_dummies",
+]
+optional = false
+version = "0.37"
+
+[dev-dependencies]
+nu-cmd-lang = { path = "../nu-cmd-lang", version = "0.92.2" }
+nu-engine = { path = "../nu-engine", version = "0.92.2" }
+nu-parser = { path = "../nu-parser", version = "0.92.2" }
+nu-command = { path = "../nu-command", version = "0.92.2" }
+nu-plugin-test-support = { path = "../nu-plugin-test-support", version = "0.92.2" }
diff --git a/crates/nu_plugin_polars/LICENSE b/crates/nu_plugin_polars/LICENSE
new file mode 100644
index 0000000000..ae174e8595
--- /dev/null
+++ b/crates/nu_plugin_polars/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2019 - 2023 The Nushell Project Developers
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/crates/nu_plugin_polars/src/cache.rs b/crates/nu_plugin_polars/src/cache.rs
new file mode 100644
index 0000000000..a1763fbba2
--- /dev/null
+++ b/crates/nu_plugin_polars/src/cache.rs
@@ -0,0 +1,122 @@
+use std::{
+    collections::HashMap,
+    sync::{Mutex, MutexGuard},
+};
+
+use nu_plugin::EngineInterface;
+use nu_protocol::{LabeledError, ShellError};
+use uuid::Uuid;
+
+use crate::{plugin_debug, values::PolarsPluginObject, PolarsPlugin};
+
+#[derive(Default)]
+pub struct Cache {
+    cache: Mutex<HashMap<Uuid, PolarsPluginObject>>,
+}
+
+impl Cache {
+    fn lock(&self) -> Result<MutexGuard<HashMap<Uuid, PolarsPluginObject>>, ShellError> {
+        self.cache.lock().map_err(|e| ShellError::GenericError {
+            error: format!("error acquiring cache lock: {e}"),
+            msg: "".into(),
+            span: None,
+            help: None,
+            inner: vec![],
+        })
+    }
+
+    /// Removes an item from the plugin cache.
+    /// The maybe_engine parameter is required outside of testing
+    pub fn remove(
+        &self,
+        maybe_engine: Option<&EngineInterface>,
+        uuid: &Uuid,
+    ) -> Result<Option<PolarsPluginObject>, ShellError> {
+        let mut lock = self.lock()?;
+        let removed = lock.remove(uuid);
+        plugin_debug!("PolarsPlugin: removing {uuid} from cache: {removed:?}");
+        // Once there are no more entries in the cache
+        // we can turn plugin gc back on
+        match maybe_engine {
+            Some(engine) if lock.is_empty() => {
+                plugin_debug!("PolarsPlugin: Cache is empty enabling GC");
+                engine.set_gc_disabled(false).map_err(LabeledError::from)?;
+            }
+            _ => (),
+        };
+        drop(lock);
+        Ok(removed)
+    }
+
+    /// Inserts an item into the plugin cache.
+    /// The maybe_engine parameter is required outside of testing
+    pub fn insert(
+        &self,
+        maybe_engine: Option<&EngineInterface>,
+        uuid: Uuid,
+        value: PolarsPluginObject,
+    ) -> Result<Option<PolarsPluginObject>, ShellError> {
+        let mut lock = self.lock()?;
+        plugin_debug!("PolarsPlugin: Inserting {uuid} into cache: {value:?}");
+        // turn off plugin gc the first time an entry is added to the cache
+        // as we don't want the plugin to be garbage collected if there
+        // is any live data
+        match maybe_engine {
+            Some(engine) if lock.is_empty() => {
+                plugin_debug!("PolarsPlugin: Cache has values disabling GC");
+                engine.set_gc_disabled(true).map_err(LabeledError::from)?;
+            }
+            _ => (),
+        };
+        let result = lock.insert(uuid, value);
+        drop(lock);
+        Ok(result)
+    }
+
+    pub fn get(&self, uuid: &Uuid) -> Result<Option<PolarsPluginObject>, ShellError> {
+        let lock = self.lock()?;
+        let result = lock.get(uuid).cloned();
+        drop(lock);
+        Ok(result)
+    }
+
+    pub fn process_entries<F, T>(&self, mut func: F) -> Result<Vec<T>, ShellError>
+    where
+        F: FnMut((&Uuid, &PolarsPluginObject)) -> Result<T, ShellError>,
+    {
+        let lock = self.lock()?;
+        let mut vals: Vec<T> = Vec::new();
+        for entry in lock.iter() {
+            eprintln!("entry: {:?}", entry);
+            let val = func(entry)?;
+            vals.push(val);
+        }
+        drop(lock);
+        Ok(vals)
+    }
+}
+
+pub trait Cacheable: Sized + Clone {
+    fn cache_id(&self) -> &Uuid;
+
+    fn to_cache_value(&self) -> Result<PolarsPluginObject, ShellError>;
+
+    fn from_cache_value(cv: PolarsPluginObject) -> Result<Self, ShellError>;
+
+    fn cache(self, plugin: &PolarsPlugin, engine: &EngineInterface) -> Result<Self, ShellError> {
+        plugin.cache.insert(
+            Some(engine),
+            self.cache_id().to_owned(),
+            self.to_cache_value()?,
+        )?;
+        Ok(self)
+    }
+
+    fn get_cached(plugin: &PolarsPlugin, id: &Uuid) -> Result<Option<Self>, ShellError> {
+        if let Some(cache_value) = plugin.cache.get(id)? {
+            Ok(Some(Self::from_cache_value(cache_value)?))
+        } else {
+            Ok(None)
+        }
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/README.md b/crates/nu_plugin_polars/src/dataframe/README.md
new file mode 100644
index 0000000000..593217ede6
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/README.md
@@ -0,0 +1,12 @@
+# Dataframe
+
+This dataframe directory holds all of the definitions of the dataframe data structures and commands.
+
+There are three sections of commands:
+
+* [eager](./eager)
+* [series](./series)
+* [values](./values)
+
+For more details see the
+[Nushell book section on dataframes](https://www.nushell.sh/book/dataframes.html)
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/append.rs b/crates/nu_plugin_polars/src/dataframe/eager/append.rs
new file mode 100644
index 0000000000..4b2ae3e0d1
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/append.rs
@@ -0,0 +1,144 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+use crate::{
+    values::{to_pipeline_data, Axis, Column, CustomValueSupport, NuDataFrame},
+    PolarsPlugin,
+};
+
+#[derive(Clone)]
+pub struct AppendDF;
+
+impl PluginCommand for AppendDF {
+    type Plugin = PolarsPlugin;
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("other", SyntaxShape::Any, "other dataframe to append")
+            .switch("col", "append as new columns instead of rows", None)
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+
+    fn name(&self) -> &str {
+        "polars append"
+    }
+
+    fn usage(&self) -> &str {
+        "Appends a new dataframe."
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Appends a dataframe as new columns",
+                example: r#"let a = ([[a b]; [1 2] [3 4]] | polars into-df);
+    $a | polars append $a"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "a_x".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b_x".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Appends a dataframe merging at the end of columns",
+                example: r#"let a = ([[a b]; [1 2] [3 4]] | polars into-df); $a | polars append $a --col"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![
+                                    Value::test_int(1),
+                                    Value::test_int(3),
+                                    Value::test_int(1),
+                                    Value::test_int(3),
+                                ],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![
+                                    Value::test_int(2),
+                                    Value::test_int(4),
+                                    Value::test_int(2),
+                                    Value::test_int(4),
+                                ],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let other: Value = call.req(0)?;
+
+    let axis = if call.has_flag("col")? {
+        Axis::Column
+    } else {
+        Axis::Row
+    };
+
+    let df_other = NuDataFrame::try_from_value_coerce(plugin, &other, call.head)?;
+    let df = NuDataFrame::try_from_pipeline(plugin, input, call.head)?;
+    let df = df.append_df(&df_other, axis, call.head)?;
+
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&AppendDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/cast.rs b/crates/nu_plugin_polars/src/dataframe/eager/cast.rs
new file mode 100644
index 0000000000..20a56680fb
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/cast.rs
@@ -0,0 +1,202 @@
+use crate::{
+    dataframe::values::{str_to_dtype, to_pipeline_data, NuExpression, NuLazyFrame},
+    values::{cant_convert_err, PolarsPluginObject, PolarsPluginType},
+    PolarsPlugin,
+};
+
+use super::super::values::NuDataFrame;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    record, Category, Example, LabeledError, PipelineData, ShellError, Signature, Span,
+    SyntaxShape, Type, Value,
+};
+use polars::prelude::*;
+
+#[derive(Clone)]
+pub struct CastDF;
+
+impl PluginCommand for CastDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars cast"
+    }
+
+    fn usage(&self) -> &str {
+        "Cast a column to a different dtype."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .required(
+                "dtype",
+                SyntaxShape::String,
+                "The dtype to cast the column to",
+            )
+            .optional(
+                "column",
+                SyntaxShape::String,
+                "The column to cast. Required when used with a dataframe.",
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Cast a column in a dataframe to a different dtype",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars cast u8 a | polars schema",
+                result: Some(Value::record(
+                    record! {
+                        "a" => Value::string("u8", Span::test_data()),
+                        "b" => Value::string("i64", Span::test_data()),
+                    },
+                    Span::test_data(),
+                )),
+            },
+            Example {
+                description: "Cast a column in a lazy dataframe to a different dtype",
+                example:
+                    "[[a b]; [1 2] [3 4]] | polars into-df | polars into-lazy | polars cast u8 a | polars schema",
+                result: Some(Value::record(
+                    record! {
+                        "a" => Value::string("u8", Span::test_data()),
+                        "b" => Value::string("i64", Span::test_data()),
+                    },
+                    Span::test_data(),
+                )),
+            },
+            Example {
+                description: "Cast a column in a expression to a different dtype",
+                example: r#"[[a b]; [1 2] [1 4]] | polars into-df | polars group-by a | polars agg [ (polars col b | polars cast u8 | polars min | polars as "b_min") ] | polars schema"#,
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuLazyFrame(lazy) => {
+                let (dtype, column_nm) = df_args(call)?;
+                command_lazy(plugin, engine, call, column_nm, dtype, lazy)
+            }
+            PolarsPluginObject::NuDataFrame(df) => {
+                let (dtype, column_nm) = df_args(call)?;
+                command_eager(plugin, engine, call, column_nm, dtype, df)
+            }
+            PolarsPluginObject::NuExpression(expr) => {
+                let dtype: String = call.req(0)?;
+                let dtype = str_to_dtype(&dtype, call.head)?;
+                let expr: NuExpression = expr.to_polars().cast(dtype).into();
+                to_pipeline_data(plugin, engine, call.head, expr)
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn df_args(call: &EvaluatedCall) -> Result<(DataType, String), ShellError> {
+    let dtype = dtype_arg(call)?;
+    let column_nm: String = call.opt(1)?.ok_or(ShellError::MissingParameter {
+        param_name: "column_name".into(),
+        span: call.head,
+    })?;
+    Ok((dtype, column_nm))
+}
+
+fn dtype_arg(call: &EvaluatedCall) -> Result<DataType, ShellError> {
+    let dtype: String = call.req(0)?;
+    str_to_dtype(&dtype, call.head)
+}
+
+fn command_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    column_nm: String,
+    dtype: DataType,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let column = col(&column_nm).cast(dtype);
+    let lazy = lazy.to_polars().with_columns(&[column]);
+    let lazy = NuLazyFrame::new(false, lazy);
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+fn command_eager(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    column_nm: String,
+    dtype: DataType,
+    nu_df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let mut df = (*nu_df.df).clone();
+    let column = df
+        .column(&column_nm)
+        .map_err(|e| ShellError::GenericError {
+            error: format!("{e}"),
+            msg: "".into(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let casted = column.cast(&dtype).map_err(|e| ShellError::GenericError {
+        error: format!("{e}"),
+        msg: "".into(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let _ = df
+        .with_column(casted)
+        .map_err(|e| ShellError::GenericError {
+            error: format!("{e}"),
+            msg: "".into(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let df = NuDataFrame::new(false, df);
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&CastDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/columns.rs b/crates/nu_plugin_polars/src/dataframe/eager/columns.rs
new file mode 100644
index 0000000000..892d3a5175
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/columns.rs
@@ -0,0 +1,79 @@
+use crate::PolarsPlugin;
+
+use super::super::values::NuDataFrame;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct ColumnsDF;
+
+impl PluginCommand for ColumnsDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars columns"
+    }
+
+    fn usage(&self) -> &str {
+        "Show dataframe columns."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(Type::Custom("dataframe".into()), Type::Any)
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Dataframe columns",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars columns",
+            result: Some(Value::list(
+                vec![Value::test_string("a"), Value::test_string("b")],
+                Span::test_data(),
+            )),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        _engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, call, input).map_err(|e| e.into())
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let names: Vec<Value> = df
+        .as_ref()
+        .get_column_names()
+        .iter()
+        .map(|v| Value::string(*v, call.head))
+        .collect();
+
+    let names = Value::list(names, call.head);
+
+    Ok(PipelineData::Value(names, None))
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ColumnsDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/drop.rs b/crates/nu_plugin_polars/src/dataframe/eager/drop.rs
new file mode 100644
index 0000000000..e8a24bb328
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/drop.rs
@@ -0,0 +1,127 @@
+use crate::values::to_pipeline_data;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+use crate::values::CustomValueSupport;
+use crate::PolarsPlugin;
+
+use super::super::values::utils::convert_columns;
+use super::super::values::{Column, NuDataFrame};
+
+#[derive(Clone)]
+pub struct DropDF;
+
+impl PluginCommand for DropDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars drop"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates a new dataframe by dropping the selected columns."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest("rest", SyntaxShape::Any, "column names to be dropped")
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "drop column a",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars drop a",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "b".to_string(),
+                        vec![Value::test_int(2), Value::test_int(4)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let columns: Vec<Value> = call.rest(0)?;
+    let (col_string, col_span) = convert_columns(columns, call.head)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let new_df = col_string
+        .first()
+        .ok_or_else(|| ShellError::GenericError {
+            error: "Empty names list".into(),
+            msg: "No column names were found".into(),
+            span: Some(col_span),
+            help: None,
+            inner: vec![],
+        })
+        .and_then(|col| {
+            df.as_ref()
+                .drop(&col.item)
+                .map_err(|e| ShellError::GenericError {
+                    error: "Error dropping column".into(),
+                    msg: e.to_string(),
+                    span: Some(col.span),
+                    help: None,
+                    inner: vec![],
+                })
+        })?;
+
+    // If there are more columns in the drop selection list, these
+    // are added from the resulting dataframe
+    let polars_df = col_string.iter().skip(1).try_fold(new_df, |new_df, col| {
+        new_df
+            .drop(&col.item)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error dropping column".into(),
+                msg: e.to_string(),
+                span: Some(col.span),
+                help: None,
+                inner: vec![],
+            })
+    })?;
+
+    let final_df = NuDataFrame::new(df.from_lazy, polars_df);
+
+    to_pipeline_data(plugin, engine, call.head, final_df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&DropDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/drop_duplicates.rs b/crates/nu_plugin_polars/src/dataframe/eager/drop_duplicates.rs
new file mode 100644
index 0000000000..57cd0ca642
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/drop_duplicates.rs
@@ -0,0 +1,133 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::UniqueKeepStrategy;
+
+use crate::values::{to_pipeline_data, CustomValueSupport};
+use crate::PolarsPlugin;
+
+use super::super::values::utils::convert_columns_string;
+use super::super::values::{Column, NuDataFrame};
+
+#[derive(Clone)]
+pub struct DropDuplicates;
+
+impl PluginCommand for DropDuplicates {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars drop-duplicates"
+    }
+
+    fn usage(&self) -> &str {
+        "Drops duplicate values in dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .optional(
+                "subset",
+                SyntaxShape::Table(vec![]),
+                "subset of columns to drop duplicates",
+            )
+            .switch("maintain", "maintain order", Some('m'))
+            .switch(
+                "last",
+                "keeps last duplicate value (by default keeps first)",
+                Some('l'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "drop duplicates",
+            example: "[[a b]; [1 2] [3 4] [1 2]] | polars into-df | polars drop-duplicates",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_int(3), Value::test_int(1)],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(4), Value::test_int(2)],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let columns: Option<Vec<Value>> = call.opt(0)?;
+    let (subset, col_span) = match columns {
+        Some(cols) => {
+            let (agg_string, col_span) = convert_columns_string(cols, call.head)?;
+            (Some(agg_string), col_span)
+        }
+        None => (None, call.head),
+    };
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let subset_slice = subset.as_ref().map(|cols| &cols[..]);
+
+    let keep_strategy = if call.has_flag("last")? {
+        UniqueKeepStrategy::Last
+    } else {
+        UniqueKeepStrategy::First
+    };
+
+    let polars_df = df
+        .as_ref()
+        .unique(subset_slice, keep_strategy, None)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error dropping duplicates".into(),
+            msg: e.to_string(),
+            span: Some(col_span),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let df = NuDataFrame::new(df.from_lazy, polars_df);
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&DropDuplicates)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/drop_nulls.rs b/crates/nu_plugin_polars/src/dataframe/eager/drop_nulls.rs
new file mode 100644
index 0000000000..fed4596338
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/drop_nulls.rs
@@ -0,0 +1,149 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+use crate::values::{to_pipeline_data, CustomValueSupport};
+use crate::PolarsPlugin;
+
+use super::super::values::utils::convert_columns_string;
+use super::super::values::{Column, NuDataFrame};
+
+#[derive(Clone)]
+pub struct DropNulls;
+
+impl PluginCommand for DropNulls {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars drop-nulls"
+    }
+
+    fn usage(&self) -> &str {
+        "Drops null values in dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .optional(
+                "subset",
+                SyntaxShape::Table(vec![]),
+                "subset of columns to drop nulls",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "drop null values in dataframe",
+                example: r#"let df = ([[a b]; [1 2] [3 0] [1 2]] | polars into-df);
+    let res = ($df.b / $df.b);
+    let a = ($df | polars with-column $res --name res);
+    $a | polars drop-nulls"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(1)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(2)],
+                            ),
+                            Column::new(
+                                "res".to_string(),
+                                vec![Value::test_int(1), Value::test_int(1)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "drop null values in dataframe",
+                example: r#"let s = ([1 2 0 0 3 4] | polars into-df);
+    ($s / $s) | polars drop-nulls"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "div_0_0".to_string(),
+                            vec![
+                                Value::test_int(1),
+                                Value::test_int(1),
+                                Value::test_int(1),
+                                Value::test_int(1),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let columns: Option<Vec<Value>> = call.opt(0)?;
+
+    let (subset, col_span) = match columns {
+        Some(cols) => {
+            let (agg_string, col_span) = convert_columns_string(cols, call.head)?;
+            (Some(agg_string), col_span)
+        }
+        None => (None, call.head),
+    };
+
+    let subset_slice = subset.as_ref().map(|cols| &cols[..]);
+
+    let polars_df = df
+        .as_ref()
+        .drop_nulls(subset_slice)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error dropping nulls".into(),
+            msg: e.to_string(),
+            span: Some(col_span),
+            help: None,
+            inner: vec![],
+        })?;
+    let df = NuDataFrame::new(df.from_lazy, polars_df);
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&DropNulls)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/dtypes.rs b/crates/nu_plugin_polars/src/dataframe/eager/dtypes.rs
new file mode 100644
index 0000000000..106200baaa
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/dtypes.rs
@@ -0,0 +1,111 @@
+use crate::PolarsPlugin;
+
+use super::super::values::{to_pipeline_data, Column, CustomValueSupport, NuDataFrame};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct DataTypes;
+
+impl PluginCommand for DataTypes {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars dtypes"
+    }
+
+    fn usage(&self) -> &str {
+        "Show dataframe data types."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Dataframe dtypes",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars dtypes",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "column".to_string(),
+                            vec![Value::test_string("a"), Value::test_string("b")],
+                        ),
+                        Column::new(
+                            "dtype".to_string(),
+                            vec![Value::test_string("i64"), Value::test_string("i64")],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let mut dtypes: Vec<Value> = Vec::new();
+    let names: Vec<Value> = df
+        .as_ref()
+        .get_column_names()
+        .iter()
+        .map(|v| {
+            let dtype = df
+                .as_ref()
+                .column(v)
+                .expect("using name from list of names from dataframe")
+                .dtype();
+
+            let dtype_str = dtype.to_string();
+
+            dtypes.push(Value::string(dtype_str, call.head));
+
+            Value::string(*v, call.head)
+        })
+        .collect();
+
+    let names_col = Column::new("column".to_string(), names);
+    let dtypes_col = Column::new("dtype".to_string(), dtypes);
+
+    let df = NuDataFrame::try_from_columns(vec![names_col, dtypes_col], None)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&DataTypes)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/dummies.rs b/crates/nu_plugin_polars/src/dataframe/eager/dummies.rs
new file mode 100644
index 0000000000..4c71f92741
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/dummies.rs
@@ -0,0 +1,119 @@
+use super::super::values::NuDataFrame;
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{prelude::*, series::Series};
+
+#[derive(Clone)]
+pub struct Dummies;
+
+impl PluginCommand for Dummies {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars dummies"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates a new dataframe with dummy variables."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .switch("drop-first", "Drop first row", Some('d'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create new dataframe with dummy variables from a dataframe",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars dummies",
+                result: Some(
+                    NuDataFrame::try_from_series_vec(
+                        vec![
+                            Series::new("a_1", &[1_u8, 0]),
+                            Series::new("a_3", &[0_u8, 1]),
+                            Series::new("b_2", &[1_u8, 0]),
+                            Series::new("b_4", &[0_u8, 1]),
+                        ],
+                        Span::test_data(),
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Create new dataframe with dummy variables from a series",
+                example: "[1 2 2 3 3] | polars into-df | polars dummies",
+                result: Some(
+                    NuDataFrame::try_from_series_vec(
+                        vec![
+                            Series::new("0_1", &[1_u8, 0, 0, 0, 0]),
+                            Series::new("0_2", &[0_u8, 1, 1, 0, 0]),
+                            Series::new("0_3", &[0_u8, 0, 0, 1, 1]),
+                        ],
+                        Span::test_data(),
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let drop_first: bool = call.has_flag("drop-first")?;
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let polars_df =
+        df.as_ref()
+            .to_dummies(None, drop_first)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error calculating dummies".into(),
+                msg: e.to_string(),
+                span: Some(call.head),
+                help: Some("The only allowed column types for dummies are String or Int".into()),
+                inner: vec![],
+            })?;
+
+    let df: NuDataFrame = polars_df.into();
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Dummies)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/filter_with.rs b/crates/nu_plugin_polars/src/dataframe/eager/filter_with.rs
new file mode 100644
index 0000000000..1dcb84053f
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/filter_with.rs
@@ -0,0 +1,165 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::LazyFrame;
+
+use crate::{
+    dataframe::values::{NuExpression, NuLazyFrame},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+#[derive(Clone)]
+pub struct FilterWith;
+
+impl PluginCommand for FilterWith {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars filter-with"
+    }
+
+    fn usage(&self) -> &str {
+        "Filters dataframe using a mask or expression as reference."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "mask or expression",
+                SyntaxShape::Any,
+                "boolean mask used to filter data",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe or lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Filter dataframe using a bool mask",
+                example: r#"let mask = ([true false] | polars into-df);
+    [[a b]; [1 2] [3 4]] | polars into-df | polars filter-with $mask"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new("a".to_string(), vec![Value::test_int(1)]),
+                            Column::new("b".to_string(), vec![Value::test_int(2)]),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Filter dataframe using an expression",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars filter-with ((polars col a) > 1)",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new("a".to_string(), vec![Value::test_int(3)]),
+                            Column::new("b".to_string(), vec![Value::test_int(4)]),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command_eager(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => command_lazy(plugin, engine, call, lazy),
+            _ => Err(cant_convert_err(
+                &value,
+                &[PolarsPluginType::NuDataFrame, PolarsPluginType::NuLazyFrame],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command_eager(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let mask_value: Value = call.req(0)?;
+    let mask_span = mask_value.span();
+
+    if NuExpression::can_downcast(&mask_value) {
+        let expression = NuExpression::try_from_value(plugin, &mask_value)?;
+        let lazy = df.lazy();
+        let lazy = lazy.apply_with_expr(expression, LazyFrame::filter);
+
+        to_pipeline_data(plugin, engine, call.head, lazy)
+    } else {
+        let mask = NuDataFrame::try_from_value_coerce(plugin, &mask_value, mask_span)?
+            .as_series(mask_span)?;
+        let mask = mask.bool().map_err(|e| ShellError::GenericError {
+            error: "Error casting to bool".into(),
+            msg: e.to_string(),
+            span: Some(mask_span),
+            help: Some("Perhaps you want to use a series with booleans as mask".into()),
+            inner: vec![],
+        })?;
+
+        let polars_df = df
+            .as_ref()
+            .filter(mask)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error filtering dataframe".into(),
+                msg: e.to_string(),
+                span: Some(call.head),
+                help: Some("The only allowed column types for dummies are String or Int".into()),
+                inner: vec![],
+            })?;
+        let df = NuDataFrame::new(df.from_lazy, polars_df);
+        to_pipeline_data(plugin, engine, call.head, df)
+    }
+}
+
+fn command_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let expr: Value = call.req(0)?;
+    let expr = NuExpression::try_from_value(plugin, &expr)?;
+    let lazy = lazy.apply_with_expr(expr, LazyFrame::filter);
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&FilterWith)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/first.rs b/crates/nu_plugin_polars/src/dataframe/eager/first.rs
new file mode 100644
index 0000000000..72a0a6cc8c
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/first.rs
@@ -0,0 +1,137 @@
+use crate::{
+    values::{to_pipeline_data, Column, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{NuDataFrame, NuExpression};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct FirstDF;
+
+impl PluginCommand for FirstDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars first"
+    }
+
+    fn usage(&self) -> &str {
+        "Show only the first number of rows or create a first expression"
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .optional(
+                "rows",
+                SyntaxShape::Int,
+                "starting from the front, the number of rows to return",
+            )
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Return the first row of a dataframe",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars first",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new("a".to_string(), vec![Value::test_int(1)]),
+                            Column::new("b".to_string(), vec![Value::test_int(2)]),
+                        ],
+                        None,
+                    )
+                    .expect("should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Return the first two rows of a dataframe",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars first 2",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates a first expression from a column",
+                example: "polars col a | polars first",
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        if NuDataFrame::can_downcast(&value) {
+            let df = NuDataFrame::try_from_value(plugin, &value)?;
+            command(plugin, engine, call, df).map_err(|e| e.into())
+        } else {
+            let expr = NuExpression::try_from_value(plugin, &value)?;
+            let expr: NuExpression = expr.to_polars().first().into();
+
+            to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+        }
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let rows: Option<usize> = call.opt(0)?;
+    let rows = rows.unwrap_or(1);
+
+    let res = df.as_ref().head(Some(rows));
+    let res = NuDataFrame::new(false, res);
+
+    to_pipeline_data(plugin, engine, call.head, res)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&FirstDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/get.rs b/crates/nu_plugin_polars/src/dataframe/eager/get.rs
new file mode 100644
index 0000000000..32b8c3143a
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/get.rs
@@ -0,0 +1,103 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+use crate::{
+    dataframe::values::utils::convert_columns_string,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+#[derive(Clone)]
+pub struct GetDF;
+
+impl PluginCommand for GetDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates dataframe with the selected columns."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest("rest", SyntaxShape::Any, "column names to sort dataframe")
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns the selected column",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars get a",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "a".to_string(),
+                        vec![Value::test_int(1), Value::test_int(3)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let columns: Vec<Value> = call.rest(0)?;
+    let (col_string, col_span) = convert_columns_string(columns, call.head)?;
+
+    let df = NuDataFrame::try_from_pipeline(plugin, input, call.head)?;
+
+    let df = df
+        .as_ref()
+        .select(col_string)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error selecting columns".into(),
+            msg: e.to_string(),
+            span: Some(col_span),
+            help: None,
+            inner: vec![],
+        })?;
+    let df = NuDataFrame::new(false, df);
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/last.rs b/crates/nu_plugin_polars/src/dataframe/eager/last.rs
new file mode 100644
index 0000000000..e9a019093b
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/last.rs
@@ -0,0 +1,112 @@
+use crate::{
+    values::{to_pipeline_data, Column, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{utils::DEFAULT_ROWS, NuDataFrame, NuExpression};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct LastDF;
+
+impl PluginCommand for LastDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars last"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates new dataframe with tail rows or creates a last expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .optional("rows", SyntaxShape::Int, "Number of rows for tail")
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create new dataframe with last rows",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars last 1",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new("a".to_string(), vec![Value::test_int(3)]),
+                            Column::new("b".to_string(), vec![Value::test_int(4)]),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates a last expression from a column",
+                example: "polars col a | polars last",
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        if NuDataFrame::can_downcast(&value) {
+            let df = NuDataFrame::try_from_value(plugin, &value)?;
+            command(plugin, engine, call, df).map_err(|e| e.into())
+        } else {
+            let expr = NuExpression::try_from_value(plugin, &value)?;
+            let expr: NuExpression = expr.to_polars().last().into();
+
+            to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+        }
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let rows: Option<usize> = call.opt(0)?;
+    let rows = rows.unwrap_or(DEFAULT_ROWS);
+
+    let res = df.as_ref().tail(Some(rows));
+    let res = NuDataFrame::new(false, res);
+    to_pipeline_data(plugin, engine, call.head, res)
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LastDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/list.rs b/crates/nu_plugin_polars/src/dataframe/eager/list.rs
new file mode 100644
index 0000000000..1548013415
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/list.rs
@@ -0,0 +1,96 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    record, Category, Example, IntoPipelineData, LabeledError, PipelineData, Signature, Value,
+};
+
+use crate::{values::PolarsPluginObject, PolarsPlugin};
+
+#[derive(Clone)]
+pub struct ListDF;
+
+impl PluginCommand for ListDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars ls"
+    }
+
+    fn usage(&self) -> &str {
+        "Lists stored dataframes."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name()).category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Creates a new dataframe and shows it in the dataframe list",
+            example: r#"let test = ([[a b];[1 2] [3 4]] | dfr into-df);
+    polars ls"#,
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        _engine: &EngineInterface,
+        call: &EvaluatedCall,
+        _input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let vals = plugin.cache.process_entries(|(key, value)| match value {
+            PolarsPluginObject::NuDataFrame(df) => Ok(Some(Value::record(
+                record! {
+                    "key" => Value::string(key.to_string(), call.head),
+                    "columns" => Value::int(df.as_ref().width() as i64, call.head),
+                    "rows" => Value::int(df.as_ref().height() as i64, call.head),
+                    "type" => Value::string("NuDataFrame", call.head),
+                },
+                call.head,
+            ))),
+            PolarsPluginObject::NuLazyFrame(lf) => {
+                let lf = lf.clone().collect(call.head)?;
+                Ok(Some(Value::record(
+                    record! {
+                        "key" => Value::string(key.to_string(), call.head),
+                        "columns" => Value::int(lf.as_ref().width() as i64, call.head),
+                        "rows" => Value::int(lf.as_ref().height() as i64, call.head),
+                        "type" => Value::string("NuLazyFrame", call.head),
+                    },
+                    call.head,
+                )))
+            }
+            PolarsPluginObject::NuExpression(_) => Ok(Some(Value::record(
+                record! {
+                    "key" => Value::string(key.to_string(), call.head),
+                    "columns" => Value::nothing(call.head),
+                    "rows" => Value::nothing(call.head),
+                    "type" => Value::string("NuExpression", call.head),
+                },
+                call.head,
+            ))),
+            PolarsPluginObject::NuLazyGroupBy(_) => Ok(Some(Value::record(
+                record! {
+                    "key" => Value::string(key.to_string(), call.head),
+                    "columns" => Value::nothing(call.head),
+                    "rows" => Value::nothing(call.head),
+                    "type" => Value::string("NuLazyGroupBy", call.head),
+                },
+                call.head,
+            ))),
+            PolarsPluginObject::NuWhen(_) => Ok(Some(Value::record(
+                record! {
+                    "key" => Value::string(key.to_string(), call.head),
+                    "columns" => Value::nothing(call.head),
+                    "rows" => Value::nothing(call.head),
+                    "type" => Value::string("NuWhen", call.head),
+                },
+                call.head,
+            ))),
+        })?;
+        let vals = vals.into_iter().flatten().collect();
+        let list = Value::list(vals, call.head);
+        Ok(list.into_pipeline_data())
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/melt.rs b/crates/nu_plugin_polars/src/dataframe/eager/melt.rs
new file mode 100644
index 0000000000..c9e13fcfea
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/melt.rs
@@ -0,0 +1,255 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Spanned,
+    SyntaxShape, Type, Value,
+};
+
+use crate::{
+    dataframe::values::utils::convert_columns_string,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+#[derive(Clone)]
+pub struct MeltDF;
+
+impl PluginCommand for MeltDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars melt"
+    }
+
+    fn usage(&self) -> &str {
+        "Unpivot a DataFrame from wide to long format."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required_named(
+                "columns",
+                SyntaxShape::Table(vec![]),
+                "column names for melting",
+                Some('c'),
+            )
+            .required_named(
+                "values",
+                SyntaxShape::Table(vec![]),
+                "column names used as value columns",
+                Some('v'),
+            )
+            .named(
+                "variable-name",
+                SyntaxShape::String,
+                "optional name for variable column",
+                Some('r'),
+            )
+            .named(
+                "value-name",
+                SyntaxShape::String,
+                "optional name for value column",
+                Some('l'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "melt dataframe",
+            example:
+                "[[a b c d]; [x 1 4 a] [y 2 5 b] [z 3 6 c]] | polars into-df | polars melt -c [b c] -v [a d]",
+            result: Some(
+                NuDataFrame::try_from_columns(vec![
+                    Column::new(
+                        "b".to_string(),
+                        vec![
+                            Value::test_int(1),
+                            Value::test_int(2),
+                            Value::test_int(3),
+                            Value::test_int(1),
+                            Value::test_int(2),
+                            Value::test_int(3),
+                        ],
+                    ),
+                    Column::new(
+                        "c".to_string(),
+                        vec![
+                            Value::test_int(4),
+                            Value::test_int(5),
+                            Value::test_int(6),
+                            Value::test_int(4),
+                            Value::test_int(5),
+                            Value::test_int(6),
+                        ],
+                    ),
+                    Column::new(
+                        "variable".to_string(),
+                        vec![
+                            Value::test_string("a"),
+                            Value::test_string("a"),
+                            Value::test_string("a"),
+                            Value::test_string("d"),
+                            Value::test_string("d"),
+                            Value::test_string("d"),
+                        ],
+                    ),
+                    Column::new(
+                        "value".to_string(),
+                        vec![
+                            Value::test_string("x"),
+                            Value::test_string("y"),
+                            Value::test_string("z"),
+                            Value::test_string("a"),
+                            Value::test_string("b"),
+                            Value::test_string("c"),
+                        ],
+                    ),
+                ], None)
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let id_col: Vec<Value> = call.get_flag("columns")?.expect("required value");
+    let val_col: Vec<Value> = call.get_flag("values")?.expect("required value");
+
+    let value_name: Option<Spanned<String>> = call.get_flag("value-name")?;
+    let variable_name: Option<Spanned<String>> = call.get_flag("variable-name")?;
+
+    let (id_col_string, id_col_span) = convert_columns_string(id_col, call.head)?;
+    let (val_col_string, val_col_span) = convert_columns_string(val_col, call.head)?;
+
+    let df = NuDataFrame::try_from_pipeline(plugin, input, call.head)?;
+
+    check_column_datatypes(df.as_ref(), &id_col_string, id_col_span)?;
+    check_column_datatypes(df.as_ref(), &val_col_string, val_col_span)?;
+
+    let mut res = df
+        .as_ref()
+        .melt(&id_col_string, &val_col_string)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error calculating melt".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+
+    if let Some(name) = &variable_name {
+        res.rename("variable", &name.item)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error renaming column".into(),
+                msg: e.to_string(),
+                span: Some(name.span),
+                help: None,
+                inner: vec![],
+            })?;
+    }
+
+    if let Some(name) = &value_name {
+        res.rename("value", &name.item)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error renaming column".into(),
+                msg: e.to_string(),
+                span: Some(name.span),
+                help: None,
+                inner: vec![],
+            })?;
+    }
+
+    let res = NuDataFrame::new(false, res);
+    to_pipeline_data(plugin, engine, call.head, res)
+}
+
+fn check_column_datatypes<T: AsRef<str>>(
+    df: &polars::prelude::DataFrame,
+    cols: &[T],
+    col_span: Span,
+) -> Result<(), ShellError> {
+    if cols.is_empty() {
+        return Err(ShellError::GenericError {
+            error: "Merge error".into(),
+            msg: "empty column list".into(),
+            span: Some(col_span),
+            help: None,
+            inner: vec![],
+        });
+    }
+
+    // Checking if they are same type
+    if cols.len() > 1 {
+        for w in cols.windows(2) {
+            let l_series = df
+                .column(w[0].as_ref())
+                .map_err(|e| ShellError::GenericError {
+                    error: "Error selecting columns".into(),
+                    msg: e.to_string(),
+                    span: Some(col_span),
+                    help: None,
+                    inner: vec![],
+                })?;
+
+            let r_series = df
+                .column(w[1].as_ref())
+                .map_err(|e| ShellError::GenericError {
+                    error: "Error selecting columns".into(),
+                    msg: e.to_string(),
+                    span: Some(col_span),
+                    help: None,
+                    inner: vec![],
+                })?;
+
+            if l_series.dtype() != r_series.dtype() {
+                return Err(ShellError::GenericError {
+                    error: "Merge error".into(),
+                    msg: "found different column types in list".into(),
+                    span: Some(col_span),
+                    help: Some(format!(
+                        "datatypes {} and {} are incompatible",
+                        l_series.dtype(),
+                        r_series.dtype()
+                    )),
+                    inner: vec![],
+                });
+            }
+        }
+    }
+
+    Ok(())
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&MeltDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/mod.rs b/crates/nu_plugin_polars/src/dataframe/eager/mod.rs
new file mode 100644
index 0000000000..33df6e5281
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/mod.rs
@@ -0,0 +1,105 @@
+mod append;
+mod cast;
+mod columns;
+mod drop;
+mod drop_duplicates;
+mod drop_nulls;
+mod dtypes;
+mod dummies;
+mod filter_with;
+mod first;
+mod get;
+mod last;
+mod list;
+mod melt;
+mod open;
+mod query_df;
+mod rename;
+mod sample;
+mod schema;
+mod shape;
+mod slice;
+mod sql_context;
+mod sql_expr;
+mod summary;
+mod take;
+mod to_arrow;
+mod to_avro;
+mod to_csv;
+mod to_df;
+mod to_json_lines;
+mod to_nu;
+mod to_parquet;
+mod with_column;
+
+use crate::PolarsPlugin;
+
+pub use self::open::OpenDataFrame;
+pub use append::AppendDF;
+pub use cast::CastDF;
+pub use columns::ColumnsDF;
+pub use drop::DropDF;
+pub use drop_duplicates::DropDuplicates;
+pub use drop_nulls::DropNulls;
+pub use dtypes::DataTypes;
+pub use dummies::Dummies;
+pub use filter_with::FilterWith;
+pub use first::FirstDF;
+pub use get::GetDF;
+pub use last::LastDF;
+pub use list::ListDF;
+pub use melt::MeltDF;
+use nu_plugin::PluginCommand;
+pub use query_df::QueryDf;
+pub use rename::RenameDF;
+pub use sample::SampleDF;
+pub use schema::SchemaCmd;
+pub use shape::ShapeDF;
+pub use slice::SliceDF;
+pub use sql_context::SQLContext;
+pub use summary::Summary;
+pub use take::TakeDF;
+pub use to_arrow::ToArrow;
+pub use to_avro::ToAvro;
+pub use to_csv::ToCSV;
+pub use to_df::ToDataFrame;
+pub use to_json_lines::ToJsonLines;
+pub use to_nu::ToNu;
+pub use to_parquet::ToParquet;
+pub use with_column::WithColumn;
+
+pub(crate) fn eager_commands() -> Vec<Box<dyn PluginCommand<Plugin = PolarsPlugin>>> {
+    vec![
+        Box::new(AppendDF),
+        Box::new(CastDF),
+        Box::new(ColumnsDF),
+        Box::new(DataTypes),
+        Box::new(DropDF),
+        Box::new(DropDuplicates),
+        Box::new(DropNulls),
+        Box::new(Dummies),
+        Box::new(FilterWith),
+        Box::new(GetDF),
+        Box::new(OpenDataFrame),
+        Box::new(MeltDF),
+        Box::new(Summary),
+        Box::new(FirstDF),
+        Box::new(LastDF),
+        Box::new(ListDF),
+        Box::new(RenameDF),
+        Box::new(SampleDF),
+        Box::new(ShapeDF),
+        Box::new(SliceDF),
+        Box::new(SchemaCmd),
+        Box::new(TakeDF),
+        Box::new(ToNu),
+        Box::new(ToArrow),
+        Box::new(ToAvro),
+        Box::new(ToDataFrame),
+        Box::new(ToCSV),
+        Box::new(ToJsonLines),
+        Box::new(ToParquet),
+        Box::new(QueryDf),
+        Box::new(WithColumn),
+    ]
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/open.rs b/crates/nu_plugin_polars/src/dataframe/eager/open.rs
new file mode 100644
index 0000000000..ec8fe6b76e
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/open.rs
@@ -0,0 +1,531 @@
+use crate::{
+    dataframe::values::NuSchema,
+    values::{cache_and_to_value, NuLazyFrame},
+    PolarsPlugin,
+};
+
+use super::super::values::NuDataFrame;
+use nu_plugin::PluginCommand;
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Spanned, SyntaxShape,
+    Type, Value,
+};
+
+use std::{fs::File, io::BufReader, path::PathBuf};
+
+use polars::prelude::{
+    CsvEncoding, CsvReader, IpcReader, JsonFormat, JsonReader, LazyCsvReader, LazyFileListReader,
+    LazyFrame, ParquetReader, ScanArgsIpc, ScanArgsParquet, SerReader,
+};
+
+use polars_io::{avro::AvroReader, prelude::ParallelStrategy};
+
+#[derive(Clone)]
+pub struct OpenDataFrame;
+
+impl PluginCommand for OpenDataFrame {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars open"
+    }
+
+    fn usage(&self) -> &str {
+        "Opens CSV, JSON, JSON lines, arrow, avro, or parquet file to create dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "file",
+                SyntaxShape::Filepath,
+                "file path to load values from",
+            )
+            .switch("lazy", "creates a lazy dataframe", Some('l'))
+            .named(
+                "type",
+                SyntaxShape::String,
+                "File type: csv, tsv, json, parquet, arrow, avro. If omitted, derive from file extension",
+                Some('t'),
+            )
+            .named(
+                "delimiter",
+                SyntaxShape::String,
+                "file delimiter character. CSV file",
+                Some('d'),
+            )
+            .switch(
+                "no-header",
+                "Indicates if file doesn't have header. CSV file",
+                None,
+            )
+            .named(
+                "infer-schema",
+                SyntaxShape::Number,
+                "Number of rows to infer the schema of the file. CSV file",
+                None,
+            )
+            .named(
+                "skip-rows",
+                SyntaxShape::Number,
+                "Number of rows to skip from file. CSV file",
+                None,
+            )
+            .named(
+                "columns",
+                SyntaxShape::List(Box::new(SyntaxShape::String)),
+                "Columns to be selected from csv file. CSV and Parquet file",
+                None,
+            )
+            .named(
+                "schema",
+                SyntaxShape::Record(vec![]),
+                r#"Polars Schema in format [{name: str}]. CSV, JSON, and JSONL files"#,
+                Some('s')
+            )
+            .input_output_type(Type::Any, Type::Custom("dataframe".into()))
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Takes a file name and creates a dataframe",
+            example: "polars open test.csv",
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &nu_plugin::EngineInterface,
+        call: &nu_plugin::EvaluatedCall,
+        _input: nu_protocol::PipelineData,
+    ) -> Result<nu_protocol::PipelineData, LabeledError> {
+        command(plugin, engine, call).map_err(|e| e.into())
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &nu_plugin::EngineInterface,
+    call: &nu_plugin::EvaluatedCall,
+) -> Result<PipelineData, ShellError> {
+    let file: Spanned<PathBuf> = call.req(0)?;
+
+    let type_option: Option<Spanned<String>> = call.get_flag("type")?;
+
+    let type_id = match &type_option {
+        Some(ref t) => Some((t.item.to_owned(), "Invalid type", t.span)),
+        None => file.item.extension().map(|e| {
+            (
+                e.to_string_lossy().into_owned(),
+                "Invalid extension",
+                file.span,
+            )
+        }),
+    };
+
+    match type_id {
+        Some((e, msg, blamed)) => match e.as_str() {
+            "csv" | "tsv" => from_csv(plugin, engine, call),
+            "parquet" | "parq" => from_parquet(plugin, engine, call),
+            "ipc" | "arrow" => from_ipc(plugin, engine, call),
+            "json" => from_json(plugin, engine, call),
+            "jsonl" => from_jsonl(plugin, engine, call),
+            "avro" => from_avro(plugin, engine, call),
+            _ => Err(ShellError::FileNotFoundCustom {
+                msg: format!(
+                    "{msg}. Supported values: csv, tsv, parquet, ipc, arrow, json, jsonl, avro"
+                ),
+                span: blamed,
+            }),
+        },
+        None => Err(ShellError::FileNotFoundCustom {
+            msg: "File without extension".into(),
+            span: file.span,
+        }),
+    }
+    .map(|value| PipelineData::Value(value, None))
+}
+
+fn from_parquet(
+    plugin: &PolarsPlugin,
+    engine: &nu_plugin::EngineInterface,
+    call: &nu_plugin::EvaluatedCall,
+) -> Result<Value, ShellError> {
+    if call.has_flag("lazy")? {
+        let file: String = call.req(0)?;
+        let args = ScanArgsParquet {
+            n_rows: None,
+            cache: true,
+            parallel: ParallelStrategy::Auto,
+            rechunk: false,
+            row_index: None,
+            low_memory: false,
+            cloud_options: None,
+            use_statistics: false,
+            hive_partitioning: false,
+        };
+
+        let df: NuLazyFrame = LazyFrame::scan_parquet(file, args)
+            .map_err(|e| ShellError::GenericError {
+                error: "Parquet reader error".into(),
+                msg: format!("{e:?}"),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?
+            .into();
+
+        cache_and_to_value(plugin, engine, call.head, df)
+    } else {
+        let file: Spanned<PathBuf> = call.req(0)?;
+        let columns: Option<Vec<String>> = call.get_flag("columns")?;
+
+        let r = File::open(&file.item).map_err(|e| ShellError::GenericError {
+            error: "Error opening file".into(),
+            msg: e.to_string(),
+            span: Some(file.span),
+            help: None,
+            inner: vec![],
+        })?;
+        let reader = ParquetReader::new(r);
+
+        let reader = match columns {
+            None => reader,
+            Some(columns) => reader.with_columns(Some(columns)),
+        };
+
+        let df: NuDataFrame = reader
+            .finish()
+            .map_err(|e| ShellError::GenericError {
+                error: "Parquet reader error".into(),
+                msg: format!("{e:?}"),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?
+            .into();
+
+        cache_and_to_value(plugin, engine, call.head, df)
+    }
+}
+
+fn from_avro(
+    plugin: &PolarsPlugin,
+    engine: &nu_plugin::EngineInterface,
+    call: &nu_plugin::EvaluatedCall,
+) -> Result<Value, ShellError> {
+    let file: Spanned<PathBuf> = call.req(0)?;
+    let columns: Option<Vec<String>> = call.get_flag("columns")?;
+
+    let r = File::open(&file.item).map_err(|e| ShellError::GenericError {
+        error: "Error opening file".into(),
+        msg: e.to_string(),
+        span: Some(file.span),
+        help: None,
+        inner: vec![],
+    })?;
+    let reader = AvroReader::new(r);
+
+    let reader = match columns {
+        None => reader,
+        Some(columns) => reader.with_columns(Some(columns)),
+    };
+
+    let df: NuDataFrame = reader
+        .finish()
+        .map_err(|e| ShellError::GenericError {
+            error: "Avro reader error".into(),
+            msg: format!("{e:?}"),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into();
+
+    cache_and_to_value(plugin, engine, call.head, df)
+}
+
+fn from_ipc(
+    plugin: &PolarsPlugin,
+    engine: &nu_plugin::EngineInterface,
+    call: &nu_plugin::EvaluatedCall,
+) -> Result<Value, ShellError> {
+    if call.has_flag("lazy")? {
+        let file: String = call.req(0)?;
+        let args = ScanArgsIpc {
+            n_rows: None,
+            cache: true,
+            rechunk: false,
+            row_index: None,
+            memmap: true,
+        };
+
+        let df: NuLazyFrame = LazyFrame::scan_ipc(file, args)
+            .map_err(|e| ShellError::GenericError {
+                error: "IPC reader error".into(),
+                msg: format!("{e:?}"),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?
+            .into();
+
+        cache_and_to_value(plugin, engine, call.head, df)
+    } else {
+        let file: Spanned<PathBuf> = call.req(0)?;
+        let columns: Option<Vec<String>> = call.get_flag("columns")?;
+
+        let r = File::open(&file.item).map_err(|e| ShellError::GenericError {
+            error: "Error opening file".into(),
+            msg: e.to_string(),
+            span: Some(file.span),
+            help: None,
+            inner: vec![],
+        })?;
+        let reader = IpcReader::new(r);
+
+        let reader = match columns {
+            None => reader,
+            Some(columns) => reader.with_columns(Some(columns)),
+        };
+
+        let df: NuDataFrame = reader
+            .finish()
+            .map_err(|e| ShellError::GenericError {
+                error: "IPC reader error".into(),
+                msg: format!("{e:?}"),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?
+            .into();
+
+        cache_and_to_value(plugin, engine, call.head, df)
+    }
+}
+
+fn from_json(
+    plugin: &PolarsPlugin,
+    engine: &nu_plugin::EngineInterface,
+    call: &nu_plugin::EvaluatedCall,
+) -> Result<Value, ShellError> {
+    let file: Spanned<PathBuf> = call.req(0)?;
+    let file = File::open(&file.item).map_err(|e| ShellError::GenericError {
+        error: "Error opening file".into(),
+        msg: e.to_string(),
+        span: Some(file.span),
+        help: None,
+        inner: vec![],
+    })?;
+    let maybe_schema = call
+        .get_flag("schema")?
+        .map(|schema| NuSchema::try_from(&schema))
+        .transpose()?;
+
+    let buf_reader = BufReader::new(file);
+    let reader = JsonReader::new(buf_reader);
+
+    let reader = match maybe_schema {
+        Some(schema) => reader.with_schema(schema.into()),
+        None => reader,
+    };
+
+    let df: NuDataFrame = reader
+        .finish()
+        .map_err(|e| ShellError::GenericError {
+            error: "Json reader error".into(),
+            msg: format!("{e:?}"),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into();
+
+    cache_and_to_value(plugin, engine, call.head, df)
+}
+
+fn from_jsonl(
+    plugin: &PolarsPlugin,
+    engine: &nu_plugin::EngineInterface,
+    call: &nu_plugin::EvaluatedCall,
+) -> Result<Value, ShellError> {
+    let infer_schema: Option<usize> = call.get_flag("infer-schema")?;
+    let maybe_schema = call
+        .get_flag("schema")?
+        .map(|schema| NuSchema::try_from(&schema))
+        .transpose()?;
+    let file: Spanned<PathBuf> = call.req(0)?;
+    let file = File::open(&file.item).map_err(|e| ShellError::GenericError {
+        error: "Error opening file".into(),
+        msg: e.to_string(),
+        span: Some(file.span),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let buf_reader = BufReader::new(file);
+    let reader = JsonReader::new(buf_reader)
+        .with_json_format(JsonFormat::JsonLines)
+        .infer_schema_len(infer_schema);
+
+    let reader = match maybe_schema {
+        Some(schema) => reader.with_schema(schema.into()),
+        None => reader,
+    };
+
+    let df: NuDataFrame = reader
+        .finish()
+        .map_err(|e| ShellError::GenericError {
+            error: "Json lines reader error".into(),
+            msg: format!("{e:?}"),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into();
+
+    cache_and_to_value(plugin, engine, call.head, df)
+}
+
+fn from_csv(
+    plugin: &PolarsPlugin,
+    engine: &nu_plugin::EngineInterface,
+    call: &nu_plugin::EvaluatedCall,
+) -> Result<Value, ShellError> {
+    let delimiter: Option<Spanned<String>> = call.get_flag("delimiter")?;
+    let no_header: bool = call.has_flag("no-header")?;
+    let infer_schema: Option<usize> = call.get_flag("infer-schema")?;
+    let skip_rows: Option<usize> = call.get_flag("skip-rows")?;
+    let columns: Option<Vec<String>> = call.get_flag("columns")?;
+
+    let maybe_schema = call
+        .get_flag("schema")?
+        .map(|schema| NuSchema::try_from(&schema))
+        .transpose()?;
+
+    if call.has_flag("lazy")? {
+        let file: String = call.req(0)?;
+        let csv_reader = LazyCsvReader::new(file);
+
+        let csv_reader = match delimiter {
+            None => csv_reader,
+            Some(d) => {
+                if d.item.len() != 1 {
+                    return Err(ShellError::GenericError {
+                        error: "Incorrect delimiter".into(),
+                        msg: "Delimiter has to be one character".into(),
+                        span: Some(d.span),
+                        help: None,
+                        inner: vec![],
+                    });
+                } else {
+                    let delimiter = match d.item.chars().next() {
+                        Some(d) => d as u8,
+                        None => unreachable!(),
+                    };
+                    csv_reader.with_separator(delimiter)
+                }
+            }
+        };
+
+        let csv_reader = csv_reader.has_header(!no_header);
+
+        let csv_reader = match maybe_schema {
+            Some(schema) => csv_reader.with_schema(Some(schema.into())),
+            None => csv_reader,
+        };
+
+        let csv_reader = match infer_schema {
+            None => csv_reader,
+            Some(r) => csv_reader.with_infer_schema_length(Some(r)),
+        };
+
+        let csv_reader = match skip_rows {
+            None => csv_reader,
+            Some(r) => csv_reader.with_skip_rows(r),
+        };
+
+        let df: NuLazyFrame = csv_reader
+            .finish()
+            .map_err(|e| ShellError::GenericError {
+                error: "Parquet reader error".into(),
+                msg: format!("{e:?}"),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?
+            .into();
+
+        cache_and_to_value(plugin, engine, call.head, df)
+    } else {
+        let file: Spanned<PathBuf> = call.req(0)?;
+        let csv_reader = CsvReader::from_path(&file.item)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error creating CSV reader".into(),
+                msg: e.to_string(),
+                span: Some(file.span),
+                help: None,
+                inner: vec![],
+            })?
+            .with_encoding(CsvEncoding::LossyUtf8);
+
+        let csv_reader = match delimiter {
+            None => csv_reader,
+            Some(d) => {
+                if d.item.len() != 1 {
+                    return Err(ShellError::GenericError {
+                        error: "Incorrect delimiter".into(),
+                        msg: "Delimiter has to be one character".into(),
+                        span: Some(d.span),
+                        help: None,
+                        inner: vec![],
+                    });
+                } else {
+                    let delimiter = match d.item.chars().next() {
+                        Some(d) => d as u8,
+                        None => unreachable!(),
+                    };
+                    csv_reader.with_separator(delimiter)
+                }
+            }
+        };
+
+        let csv_reader = csv_reader.has_header(!no_header);
+
+        let csv_reader = match maybe_schema {
+            Some(schema) => csv_reader.with_schema(Some(schema.into())),
+            None => csv_reader,
+        };
+
+        let csv_reader = match infer_schema {
+            None => csv_reader,
+            Some(r) => csv_reader.infer_schema(Some(r)),
+        };
+
+        let csv_reader = match skip_rows {
+            None => csv_reader,
+            Some(r) => csv_reader.with_skip_rows(r),
+        };
+
+        let csv_reader = match columns {
+            None => csv_reader,
+            Some(columns) => csv_reader.with_columns(Some(columns)),
+        };
+
+        let df: NuDataFrame = csv_reader
+            .finish()
+            .map_err(|e| ShellError::GenericError {
+                error: "Parquet reader error".into(),
+                msg: format!("{e:?}"),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?
+            .into();
+
+        cache_and_to_value(plugin, engine, call.head, df)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/query_df.rs b/crates/nu_plugin_polars/src/dataframe/eager/query_df.rs
new file mode 100644
index 0000000000..a568a17b9b
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/query_df.rs
@@ -0,0 +1,108 @@
+use super::super::values::NuDataFrame;
+use crate::dataframe::values::Column;
+use crate::dataframe::{eager::SQLContext, values::NuLazyFrame};
+use crate::values::{to_pipeline_data, CustomValueSupport};
+use crate::PolarsPlugin;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+// attribution:
+// sql_context.rs, and sql_expr.rs were copied from polars-sql. thank you.
+// maybe we should just use the crate at some point but it's not published yet.
+// https://github.com/pola-rs/polars/tree/master/polars-sql
+
+#[derive(Clone)]
+pub struct QueryDf;
+
+impl PluginCommand for QueryDf {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars query"
+    }
+
+    fn usage(&self) -> &str {
+        "Query dataframe using SQL. Note: The dataframe is always named 'df' in your query's from clause."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("sql", SyntaxShape::String, "sql query")
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["dataframe", "sql", "search"]
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Query dataframe using SQL",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars query 'select a from df'",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "a".to_string(),
+                        vec![Value::test_int(1), Value::test_int(3)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &PolarsPlugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let sql_query: String = call.req(0)?;
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let mut ctx = SQLContext::new();
+    ctx.register("df", &df.df);
+    let df_sql = ctx
+        .execute(&sql_query)
+        .map_err(|e| ShellError::GenericError {
+            error: "Dataframe Error".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+    let lazy = NuLazyFrame::new(!df.from_lazy, df_sql);
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&QueryDf)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/rename.rs b/crates/nu_plugin_polars/src/dataframe/eager/rename.rs
new file mode 100644
index 0000000000..a2ef981664
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/rename.rs
@@ -0,0 +1,203 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+use crate::{
+    dataframe::{utils::extract_strings, values::NuLazyFrame},
+    values::{to_pipeline_data, CustomValueSupport, PolarsPluginObject},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+#[derive(Clone)]
+pub struct RenameDF;
+
+impl PluginCommand for RenameDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars rename"
+    }
+
+    fn usage(&self) -> &str {
+        "Rename a dataframe column."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "columns",
+                SyntaxShape::Any,
+                "Column(s) to be renamed. A string or list of strings",
+            )
+            .required(
+                "new names",
+                SyntaxShape::Any,
+                "New names for the selected column(s). A string or list of strings",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe or lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Renames a series",
+                example: "[5 6 7 8] | polars into-df | polars rename '0' new_name",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "new_name".to_string(),
+                            vec![
+                                Value::test_int(5),
+                                Value::test_int(6),
+                                Value::test_int(7),
+                                Value::test_int(8),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Renames a dataframe column",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars rename a a_new",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a_new".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Renames two dataframe columns",
+                example:
+                    "[[a b]; [1 2] [3 4]] | polars into-df | polars rename [a b] [a_new b_new]",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a_new".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b_new".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        match PolarsPluginObject::try_from_value(plugin, &value).map_err(LabeledError::from)? {
+            PolarsPluginObject::NuDataFrame(df) => {
+                command_eager(plugin, engine, call, df).map_err(LabeledError::from)
+            }
+            PolarsPluginObject::NuLazyFrame(lazy) => {
+                command_lazy(plugin, engine, call, lazy).map_err(LabeledError::from)
+            }
+            _ => Err(LabeledError::new(format!("Unsupported type: {value:?}"))
+                .with_label("Unsupported Type", call.head)),
+        }
+    }
+}
+
+fn command_eager(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let columns: Value = call.req(0)?;
+    let columns = extract_strings(columns)?;
+
+    let new_names: Value = call.req(1)?;
+    let new_names = extract_strings(new_names)?;
+
+    let mut polars_df = df.to_polars();
+
+    for (from, to) in columns.iter().zip(new_names.iter()) {
+        polars_df
+            .rename(from, to)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error renaming".into(),
+                msg: e.to_string(),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?;
+    }
+
+    let df = NuDataFrame::new(false, polars_df);
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+fn command_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let columns: Value = call.req(0)?;
+    let columns = extract_strings(columns)?;
+
+    let new_names: Value = call.req(1)?;
+    let new_names = extract_strings(new_names)?;
+
+    if columns.len() != new_names.len() {
+        let value: Value = call.req(1)?;
+        return Err(ShellError::IncompatibleParametersSingle {
+            msg: "New name list has different size to column list".into(),
+            span: value.span(),
+        });
+    }
+
+    let lazy = lazy.to_polars();
+    let lazy: NuLazyFrame = lazy.rename(&columns, &new_names).into();
+
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&RenameDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/sample.rs b/crates/nu_plugin_polars/src/dataframe/eager/sample.rs
new file mode 100644
index 0000000000..3ad7514251
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/sample.rs
@@ -0,0 +1,138 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Spanned, SyntaxShape,
+    Type,
+};
+use polars::prelude::NamedFrom;
+use polars::series::Series;
+
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct SampleDF;
+
+impl PluginCommand for SampleDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars sample"
+    }
+
+    fn usage(&self) -> &str {
+        "Create sample dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .named(
+                "n-rows",
+                SyntaxShape::Int,
+                "number of rows to be taken from dataframe",
+                Some('n'),
+            )
+            .named(
+                "fraction",
+                SyntaxShape::Number,
+                "fraction of dataframe to be taken",
+                Some('f'),
+            )
+            .named(
+                "seed",
+                SyntaxShape::Number,
+                "seed for the selection",
+                Some('s'),
+            )
+            .switch("replace", "sample with replace", Some('e'))
+            .switch("shuffle", "shuffle sample", Some('u'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Sample rows from dataframe",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars sample --n-rows 1",
+                result: None, // No expected value because sampling is random
+            },
+            Example {
+                description: "Shows sample row using fraction and replace",
+                example:
+                    "[[a b]; [1 2] [3 4] [5 6]] | polars into-df | polars sample --fraction 0.5 --replace",
+                result: None, // No expected value because sampling is random
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let rows: Option<Spanned<i64>> = call.get_flag("n-rows")?;
+    let fraction: Option<Spanned<f64>> = call.get_flag("fraction")?;
+    let seed: Option<u64> = call.get_flag::<i64>("seed")?.map(|val| val as u64);
+    let replace: bool = call.has_flag("replace")?;
+    let shuffle: bool = call.has_flag("shuffle")?;
+
+    let df = NuDataFrame::try_from_pipeline(plugin, input, call.head)?;
+
+    let df = match (rows, fraction) {
+        (Some(rows), None) => df
+            .as_ref()
+            .sample_n(&Series::new("s", &[rows.item]), replace, shuffle, seed)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error creating sample".into(),
+                msg: e.to_string(),
+                span: Some(rows.span),
+                help: None,
+                inner: vec![],
+            }),
+        (None, Some(frac)) => df
+            .as_ref()
+            .sample_frac(&Series::new("frac", &[frac.item]), replace, shuffle, seed)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error creating sample".into(),
+                msg: e.to_string(),
+                span: Some(frac.span),
+                help: None,
+                inner: vec![],
+            }),
+        (Some(_), Some(_)) => Err(ShellError::GenericError {
+            error: "Incompatible flags".into(),
+            msg: "Only one selection criterion allowed".into(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        }),
+        (None, None) => Err(ShellError::GenericError {
+            error: "No selection".into(),
+            msg: "No selection criterion was found".into(),
+            span: Some(call.head),
+            help: Some("Perhaps you want to use the flag -n or -f".into()),
+            inner: vec![],
+        }),
+    };
+    let df = NuDataFrame::new(false, df?);
+    to_pipeline_data(plugin, engine, call.head, df)
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/schema.rs b/crates/nu_plugin_polars/src/dataframe/eager/schema.rs
new file mode 100644
index 0000000000..b55d8ee5e2
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/schema.rs
@@ -0,0 +1,133 @@
+use crate::{values::PolarsPluginObject, PolarsPlugin};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    record, Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct SchemaCmd;
+
+impl PluginCommand for SchemaCmd {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars schema"
+    }
+
+    fn usage(&self) -> &str {
+        "Show schema for a dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .switch("datatype-list", "creates a lazy dataframe", Some('l'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Dataframe schema",
+            example: r#"[[a b]; [1 "foo"] [3 "bar"]] | polars into-df | polars schema"#,
+            result: Some(Value::record(
+                record! {
+                    "a" => Value::string("i64", Span::test_data()),
+                    "b" => Value::string("str", Span::test_data()),
+                },
+                Span::test_data(),
+            )),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        if call.has_flag("datatype-list")? {
+            Ok(PipelineData::Value(datatype_list(Span::unknown()), None))
+        } else {
+            command(plugin, engine, call, input).map_err(LabeledError::from)
+        }
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    _engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    match PolarsPluginObject::try_from_pipeline(plugin, input, call.head)? {
+        PolarsPluginObject::NuDataFrame(df) => {
+            let schema = df.schema();
+            let value: Value = schema.into();
+            Ok(PipelineData::Value(value, None))
+        }
+        PolarsPluginObject::NuLazyFrame(lazy) => {
+            let schema = lazy.schema()?;
+            let value: Value = schema.into();
+            Ok(PipelineData::Value(value, None))
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Must be a dataframe or lazy dataframe".into(),
+            msg: "".into(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn datatype_list(span: Span) -> Value {
+    let types: Vec<Value> = [
+        ("null", ""),
+        ("bool", ""),
+        ("u8", ""),
+        ("u16", ""),
+        ("u32", ""),
+        ("u64", ""),
+        ("i8", ""),
+        ("i16", ""),
+        ("i32", ""),
+        ("i64", ""),
+        ("f32", ""),
+        ("f64", ""),
+        ("str", ""),
+        ("binary", ""),
+        ("date", ""),
+        ("datetime<time_unit: (ms, us, ns) timezone (optional)>", "Time Unit can be: milliseconds: ms, microseconds: us, nanoseconds: ns. Timezone wildcard is *. Other Timezone examples: UTC, America/Los_Angeles."),
+        ("duration<time_unit: (ms, us, ns)>", "Time Unit can be: milliseconds: ms, microseconds: us, nanoseconds: ns."),
+        ("time", ""),
+        ("object", ""),
+        ("unknown", ""),
+        ("list<dtype>", ""),
+    ]
+    .iter()
+    .map(|(dtype, note)| {
+        Value::record(record! {
+            "dtype" => Value::string(*dtype, span),
+            "note" => Value::string(*note, span),
+        },
+        span)
+    })
+    .collect();
+    Value::list(types, span)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&SchemaCmd)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/shape.rs b/crates/nu_plugin_polars/src/dataframe/eager/shape.rs
new file mode 100644
index 0000000000..7be6d2088c
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/shape.rs
@@ -0,0 +1,94 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+use crate::{
+    dataframe::values::Column,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct ShapeDF;
+
+impl PluginCommand for ShapeDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars shape"
+    }
+
+    fn usage(&self) -> &str {
+        "Shows column and row size for a dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Shows row and column shape",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars shape",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("rows".to_string(), vec![Value::test_int(2)]),
+                        Column::new("columns".to_string(), vec![Value::test_int(2)]),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let rows = Value::int(df.as_ref().height() as i64, call.head);
+
+    let cols = Value::int(df.as_ref().width() as i64, call.head);
+
+    let rows_col = Column::new("rows".to_string(), vec![rows]);
+    let cols_col = Column::new("columns".to_string(), vec![cols]);
+
+    let df = NuDataFrame::try_from_columns(vec![rows_col, cols_col], None)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ShapeDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/slice.rs b/crates/nu_plugin_polars/src/dataframe/eager/slice.rs
new file mode 100644
index 0000000000..38370703c8
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/slice.rs
@@ -0,0 +1,95 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+use crate::{
+    dataframe::values::Column,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct SliceDF;
+
+impl PluginCommand for SliceDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars slice"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates new dataframe from a slice of rows."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("offset", SyntaxShape::Int, "start of slice")
+            .required("size", SyntaxShape::Int, "size of slice")
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Create new dataframe from a slice of the rows",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars slice 0 1",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("a".to_string(), vec![Value::test_int(1)]),
+                        Column::new("b".to_string(), vec![Value::test_int(2)]),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let offset: i64 = call.req(0)?;
+    let size: usize = call.req(1)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let res = df.as_ref().slice(offset, size);
+    let res = NuDataFrame::new(false, res);
+
+    to_pipeline_data(plugin, engine, call.head, res)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&SliceDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/sql_context.rs b/crates/nu_plugin_polars/src/dataframe/eager/sql_context.rs
new file mode 100644
index 0000000000..f558904344
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/sql_context.rs
@@ -0,0 +1,228 @@
+use crate::dataframe::eager::sql_expr::parse_sql_expr;
+use polars::error::{ErrString, PolarsError};
+use polars::prelude::{col, DataFrame, DataType, IntoLazy, LazyFrame};
+use sqlparser::ast::{
+    Expr as SqlExpr, GroupByExpr, Select, SelectItem, SetExpr, Statement, TableFactor,
+    Value as SQLValue,
+};
+use sqlparser::dialect::GenericDialect;
+use sqlparser::parser::Parser;
+use std::collections::HashMap;
+
+#[derive(Default)]
+pub struct SQLContext {
+    table_map: HashMap<String, LazyFrame>,
+    dialect: GenericDialect,
+}
+
+impl SQLContext {
+    pub fn new() -> Self {
+        Self {
+            table_map: HashMap::new(),
+            dialect: GenericDialect,
+        }
+    }
+
+    pub fn register(&mut self, name: &str, df: &DataFrame) {
+        self.table_map.insert(name.to_owned(), df.clone().lazy());
+    }
+
+    fn execute_select(&self, select_stmt: &Select) -> Result<LazyFrame, PolarsError> {
+        // Determine involved dataframe
+        // Implicit join require some more work in query parsers, Explicit join are preferred for now.
+        let tbl = select_stmt.from.first().ok_or_else(|| {
+            PolarsError::ComputeError(ErrString::from("No table found in select statement"))
+        })?;
+        let mut alias_map = HashMap::new();
+        let tbl_name = match &tbl.relation {
+            TableFactor::Table { name, alias, .. } => {
+                let tbl_name = name
+                    .0
+                    .first()
+                    .ok_or_else(|| {
+                        PolarsError::ComputeError(ErrString::from(
+                            "No table found in select statement",
+                        ))
+                    })?
+                    .value
+                    .to_string();
+                if self.table_map.contains_key(&tbl_name) {
+                    if let Some(alias) = alias {
+                        alias_map.insert(alias.name.value.clone(), tbl_name.to_owned());
+                    };
+                    tbl_name
+                } else {
+                    return Err(PolarsError::ComputeError(
+                        format!("Table name {tbl_name} was not found").into(),
+                    ));
+                }
+            }
+            // Support bare table, optional with alias for now
+            _ => return Err(PolarsError::ComputeError("Not implemented".into())),
+        };
+        let df = &self.table_map[&tbl_name];
+        let mut raw_projection_before_alias: HashMap<String, usize> = HashMap::new();
+        let mut contain_wildcard = false;
+        // Filter Expression
+        let df = match select_stmt.selection.as_ref() {
+            Some(expr) => {
+                let filter_expression = parse_sql_expr(expr)?;
+                df.clone().filter(filter_expression)
+            }
+            None => df.clone(),
+        };
+        // Column Projections
+        let projection = select_stmt
+            .projection
+            .iter()
+            .enumerate()
+            .map(|(i, select_item)| {
+                Ok(match select_item {
+                    SelectItem::UnnamedExpr(expr) => {
+                        let expr = parse_sql_expr(expr)?;
+                        raw_projection_before_alias.insert(format!("{expr:?}"), i);
+                        expr
+                    }
+                    SelectItem::ExprWithAlias { expr, alias } => {
+                        let expr = parse_sql_expr(expr)?;
+                        raw_projection_before_alias.insert(format!("{expr:?}"), i);
+                        expr.alias(&alias.value)
+                    }
+                    SelectItem::QualifiedWildcard(_, _) | SelectItem::Wildcard(_) => {
+                        contain_wildcard = true;
+                        col("*")
+                    }
+                })
+            })
+            .collect::<Result<Vec<_>, PolarsError>>()?;
+        // Check for group by
+        // After projection since there might be number.
+        let group_by = match &select_stmt.group_by {
+                GroupByExpr::All =>
+                  Err(
+                      PolarsError::ComputeError("Group-By Error: Only positive number or expression are supported, not all".into())
+                  )?,
+                GroupByExpr::Expressions(expressions) => expressions
+            }
+            .iter()
+            .map(
+                |e|match e {
+                  SqlExpr::Value(SQLValue::Number(idx, _)) => {
+                    let idx = match idx.parse::<usize>() {
+                        Ok(0)| Err(_) => Err(
+                        PolarsError::ComputeError(
+                            format!("Group-By Error: Only positive number or expression are supported, got {idx}").into()
+                        )),
+                        Ok(idx) => Ok(idx)
+                    }?;
+                    Ok(projection[idx].clone())
+                  }
+                  SqlExpr::Value(_) => Err(
+                      PolarsError::ComputeError("Group-By Error: Only positive number or expression are supported".into())
+                  ),
+                  _ => parse_sql_expr(e)
+                }
+            )
+            .collect::<Result<Vec<_>, PolarsError>>()?;
+
+        let df = if group_by.is_empty() {
+            df.select(projection)
+        } else {
+            // check groupby and projection due to difference between SQL and polars
+            // Return error on wild card, shouldn't process this
+            if contain_wildcard {
+                return Err(PolarsError::ComputeError(
+                    "Group-By Error: Can't process wildcard in group-by".into(),
+                ));
+            }
+            // Default polars group by will have group by columns at the front
+            // need some container to contain position of group by columns and its position
+            // at the final agg projection, check the schema for the existence of group by column
+            // and its projections columns, keeping the original index
+            let (exclude_expr, groupby_pos): (Vec<_>, Vec<_>) = group_by
+                .iter()
+                .map(|expr| raw_projection_before_alias.get(&format!("{expr:?}")))
+                .enumerate()
+                .filter(|(_, proj_p)| proj_p.is_some())
+                .map(|(gb_p, proj_p)| (*proj_p.unwrap_or(&0), (*proj_p.unwrap_or(&0), gb_p)))
+                .unzip();
+            let (agg_projection, agg_proj_pos): (Vec<_>, Vec<_>) = projection
+                .iter()
+                .enumerate()
+                .filter(|(i, _)| !exclude_expr.contains(i))
+                .enumerate()
+                .map(|(agg_pj, (proj_p, expr))| (expr.clone(), (proj_p, agg_pj + group_by.len())))
+                .unzip();
+            let agg_df = df.group_by(group_by).agg(agg_projection);
+            let mut final_proj_pos = groupby_pos
+                .into_iter()
+                .chain(agg_proj_pos)
+                .collect::<Vec<_>>();
+
+            final_proj_pos.sort_by(|(proj_pa, _), (proj_pb, _)| proj_pa.cmp(proj_pb));
+            let final_proj = final_proj_pos
+                .into_iter()
+                .map(|(_, shm_p)| {
+                    col(agg_df
+                        .clone()
+                        // FIXME: had to do this mess to get get_index to work, not sure why. need help
+                        .collect()
+                        .unwrap_or_default()
+                        .schema()
+                        .get_at_index(shm_p)
+                        .unwrap_or((&"".into(), &DataType::Null))
+                        .0)
+                })
+                .collect::<Vec<_>>();
+            agg_df.select(final_proj)
+        };
+        Ok(df)
+    }
+
+    pub fn execute(&self, query: &str) -> Result<LazyFrame, PolarsError> {
+        let ast = Parser::parse_sql(&self.dialect, query)
+            .map_err(|e| PolarsError::ComputeError(format!("{e:?}").into()))?;
+        if ast.len() != 1 {
+            Err(PolarsError::ComputeError(
+                "One and only one statement at a time please".into(),
+            ))
+        } else {
+            let ast = ast
+                .first()
+                .ok_or_else(|| PolarsError::ComputeError(ErrString::from("No statement found")))?;
+            Ok(match ast {
+                Statement::Query(query) => {
+                    let rs = match &*query.body {
+                        SetExpr::Select(select_stmt) => self.execute_select(select_stmt)?,
+                        _ => {
+                            return Err(PolarsError::ComputeError(
+                                "INSERT, UPDATE is not supported for polars".into(),
+                            ))
+                        }
+                    };
+                    match &query.limit {
+                        Some(SqlExpr::Value(SQLValue::Number(nrow, _))) => {
+                            let nrow = nrow.parse().map_err(|err| {
+                                PolarsError::ComputeError(
+                                    format!("Conversion Error: {err:?}").into(),
+                                )
+                            })?;
+                            rs.limit(nrow)
+                        }
+                        None => rs,
+                        _ => {
+                            return Err(PolarsError::ComputeError(
+                                "Only support number argument to LIMIT clause".into(),
+                            ))
+                        }
+                    }
+                }
+                _ => {
+                    return Err(PolarsError::ComputeError(
+                        format!("Statement type {ast:?} is not supported").into(),
+                    ))
+                }
+            })
+        }
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/sql_expr.rs b/crates/nu_plugin_polars/src/dataframe/eager/sql_expr.rs
new file mode 100644
index 0000000000..9c0728ea5f
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/sql_expr.rs
@@ -0,0 +1,200 @@
+use polars::error::PolarsError;
+use polars::prelude::{col, lit, DataType, Expr, LiteralValue, PolarsResult as Result, TimeUnit};
+
+use sqlparser::ast::{
+    ArrayElemTypeDef, BinaryOperator as SQLBinaryOperator, DataType as SQLDataType,
+    Expr as SqlExpr, Function as SQLFunction, Value as SqlValue, WindowType,
+};
+
+fn map_sql_polars_datatype(data_type: &SQLDataType) -> Result<DataType> {
+    Ok(match data_type {
+        SQLDataType::Char(_)
+        | SQLDataType::Varchar(_)
+        | SQLDataType::Uuid
+        | SQLDataType::Clob(_)
+        | SQLDataType::Text
+        | SQLDataType::String(_) => DataType::String,
+        SQLDataType::Float(_) => DataType::Float32,
+        SQLDataType::Real => DataType::Float32,
+        SQLDataType::Double => DataType::Float64,
+        SQLDataType::TinyInt(_) => DataType::Int8,
+        SQLDataType::UnsignedTinyInt(_) => DataType::UInt8,
+        SQLDataType::SmallInt(_) => DataType::Int16,
+        SQLDataType::UnsignedSmallInt(_) => DataType::UInt16,
+        SQLDataType::Int(_) => DataType::Int32,
+        SQLDataType::UnsignedInt(_) => DataType::UInt32,
+        SQLDataType::BigInt(_) => DataType::Int64,
+        SQLDataType::UnsignedBigInt(_) => DataType::UInt64,
+
+        SQLDataType::Boolean => DataType::Boolean,
+        SQLDataType::Date => DataType::Date,
+        SQLDataType::Time(_, _) => DataType::Time,
+        SQLDataType::Timestamp(_, _) => DataType::Datetime(TimeUnit::Microseconds, None),
+        SQLDataType::Interval => DataType::Duration(TimeUnit::Microseconds),
+        SQLDataType::Array(array_type_def) => match array_type_def {
+            ArrayElemTypeDef::AngleBracket(inner_type)
+            | ArrayElemTypeDef::SquareBracket(inner_type) => {
+                DataType::List(Box::new(map_sql_polars_datatype(inner_type)?))
+            }
+            _ => {
+                return Err(PolarsError::ComputeError(
+                    "SQL Datatype Array(None) was not supported in polars-sql yet!".into(),
+                ))
+            }
+        },
+        _ => {
+            return Err(PolarsError::ComputeError(
+                format!("SQL Datatype {data_type:?} was not supported in polars-sql yet!").into(),
+            ))
+        }
+    })
+}
+
+fn cast_(expr: Expr, data_type: &SQLDataType) -> Result<Expr> {
+    let polars_type = map_sql_polars_datatype(data_type)?;
+    Ok(expr.cast(polars_type))
+}
+
+fn binary_op_(left: Expr, right: Expr, op: &SQLBinaryOperator) -> Result<Expr> {
+    Ok(match op {
+        SQLBinaryOperator::Plus => left + right,
+        SQLBinaryOperator::Minus => left - right,
+        SQLBinaryOperator::Multiply => left * right,
+        SQLBinaryOperator::Divide => left / right,
+        SQLBinaryOperator::Modulo => left % right,
+        SQLBinaryOperator::StringConcat => {
+            left.cast(DataType::String) + right.cast(DataType::String)
+        }
+        SQLBinaryOperator::Gt => left.gt(right),
+        SQLBinaryOperator::Lt => left.lt(right),
+        SQLBinaryOperator::GtEq => left.gt_eq(right),
+        SQLBinaryOperator::LtEq => left.lt_eq(right),
+        SQLBinaryOperator::Eq => left.eq(right),
+        SQLBinaryOperator::NotEq => left.eq(right).not(),
+        SQLBinaryOperator::And => left.and(right),
+        SQLBinaryOperator::Or => left.or(right),
+        SQLBinaryOperator::Xor => left.xor(right),
+        _ => {
+            return Err(PolarsError::ComputeError(
+                format!("SQL Operator {op:?} was not supported in polars-sql yet!").into(),
+            ))
+        }
+    })
+}
+
+fn literal_expr(value: &SqlValue) -> Result<Expr> {
+    Ok(match value {
+        SqlValue::Number(s, _) => {
+            // Check for existence of decimal separator dot
+            if s.contains('.') {
+                s.parse::<f64>().map(lit).map_err(|_| {
+                    PolarsError::ComputeError(format!("Can't parse literal {s:?}").into())
+                })
+            } else {
+                s.parse::<i64>().map(lit).map_err(|_| {
+                    PolarsError::ComputeError(format!("Can't parse literal {s:?}").into())
+                })
+            }?
+        }
+        SqlValue::SingleQuotedString(s) => lit(s.clone()),
+        SqlValue::NationalStringLiteral(s) => lit(s.clone()),
+        SqlValue::HexStringLiteral(s) => lit(s.clone()),
+        SqlValue::DoubleQuotedString(s) => lit(s.clone()),
+        SqlValue::Boolean(b) => lit(*b),
+        SqlValue::Null => Expr::Literal(LiteralValue::Null),
+        _ => {
+            return Err(PolarsError::ComputeError(
+                format!("Parsing SQL Value {value:?} was not supported in polars-sql yet!").into(),
+            ))
+        }
+    })
+}
+
+pub fn parse_sql_expr(expr: &SqlExpr) -> Result<Expr> {
+    Ok(match expr {
+        SqlExpr::Identifier(e) => col(&e.value),
+        SqlExpr::BinaryOp { left, op, right } => {
+            let left = parse_sql_expr(left)?;
+            let right = parse_sql_expr(right)?;
+            binary_op_(left, right, op)?
+        }
+        SqlExpr::Function(sql_function) => parse_sql_function(sql_function)?,
+        SqlExpr::Cast {
+            expr,
+            data_type,
+            format: _,
+        } => cast_(parse_sql_expr(expr)?, data_type)?,
+        SqlExpr::Nested(expr) => parse_sql_expr(expr)?,
+        SqlExpr::Value(value) => literal_expr(value)?,
+        _ => {
+            return Err(PolarsError::ComputeError(
+                format!("Expression: {expr:?} was not supported in polars-sql yet!").into(),
+            ))
+        }
+    })
+}
+
+fn apply_window_spec(expr: Expr, window_type: Option<&WindowType>) -> Result<Expr> {
+    Ok(match &window_type {
+        Some(wtype) => match wtype {
+            WindowType::WindowSpec(window_spec) => {
+                // Process for simple window specification, partition by first
+                let partition_by = window_spec
+                    .partition_by
+                    .iter()
+                    .map(parse_sql_expr)
+                    .collect::<Result<Vec<_>>>()?;
+                expr.over(partition_by)
+                // Order by and Row range may not be supported at the moment
+            }
+            // TODO: make NamedWindow work
+            WindowType::NamedWindow(_named) => {
+                return Err(PolarsError::ComputeError(
+                    format!("Expression: {expr:?} was not supported in polars-sql yet!").into(),
+                ))
+            }
+        },
+        None => expr,
+    })
+}
+
+fn parse_sql_function(sql_function: &SQLFunction) -> Result<Expr> {
+    use sqlparser::ast::{FunctionArg, FunctionArgExpr};
+    // Function name mostly do not have name space, so it mostly take the first args
+    let function_name = sql_function.name.0[0].value.to_ascii_lowercase();
+    let args = sql_function
+        .args
+        .iter()
+        .map(|arg| match arg {
+            FunctionArg::Named { arg, .. } => arg,
+            FunctionArg::Unnamed(arg) => arg,
+        })
+        .collect::<Vec<_>>();
+    Ok(
+        match (
+            function_name.as_str(),
+            args.as_slice(),
+            sql_function.distinct,
+        ) {
+            ("sum", [FunctionArgExpr::Expr(expr)], false) => {
+                apply_window_spec(parse_sql_expr(expr)?, sql_function.over.as_ref())?.sum()
+            }
+            ("count", [FunctionArgExpr::Expr(expr)], false) => {
+                apply_window_spec(parse_sql_expr(expr)?, sql_function.over.as_ref())?.count()
+            }
+            ("count", [FunctionArgExpr::Expr(expr)], true) => {
+                apply_window_spec(parse_sql_expr(expr)?, sql_function.over.as_ref())?.n_unique()
+            }
+            // Special case for wildcard args to count function.
+            ("count", [FunctionArgExpr::Wildcard], false) => lit(1i32).count(),
+            _ => {
+                return Err(PolarsError::ComputeError(
+                    format!(
+                        "Function {function_name:?} with args {args:?} was not supported in polars-sql yet!"
+                    )
+                    .into(),
+                ))
+            }
+        },
+    )
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/summary.rs b/crates/nu_plugin_polars/src/dataframe/eager/summary.rs
new file mode 100644
index 0000000000..dd1ad3df61
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/summary.rs
@@ -0,0 +1,293 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::{
+    chunked_array::ChunkedArray,
+    prelude::{
+        AnyValue, DataFrame, DataType, Float64Type, IntoSeries, NewChunkedArray,
+        QuantileInterpolOptions, Series, StringType,
+    },
+};
+
+#[derive(Clone)]
+pub struct Summary;
+
+impl PluginCommand for Summary {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars summary"
+    }
+
+    fn usage(&self) -> &str {
+        "For a dataframe, produces descriptive statistics (summary statistics) for its numeric columns."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .category(Category::Custom("dataframe".into()))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .named(
+                "quantiles",
+                SyntaxShape::Table(vec![]),
+                "provide optional quantiles",
+                Some('q'),
+            )
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "list dataframe descriptives",
+            example: "[[a b]; [1 1] [1 1]] | polars into-df | polars summary",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "descriptor".to_string(),
+                            vec![
+                                Value::test_string("count"),
+                                Value::test_string("sum"),
+                                Value::test_string("mean"),
+                                Value::test_string("median"),
+                                Value::test_string("std"),
+                                Value::test_string("min"),
+                                Value::test_string("25%"),
+                                Value::test_string("50%"),
+                                Value::test_string("75%"),
+                                Value::test_string("max"),
+                            ],
+                        ),
+                        Column::new(
+                            "a (i64)".to_string(),
+                            vec![
+                                Value::test_float(2.0),
+                                Value::test_float(2.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(0.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                            ],
+                        ),
+                        Column::new(
+                            "b (i64)".to_string(),
+                            vec![
+                                Value::test_float(2.0),
+                                Value::test_float(2.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(0.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                                Value::test_float(1.0),
+                            ],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let quantiles: Option<Vec<Value>> = call.get_flag("quantiles")?;
+    let quantiles = quantiles.map(|values| {
+        values
+            .iter()
+            .map(|value| {
+                let span = value.span();
+                match value {
+                    Value::Float { val, .. } => {
+                        if (&0.0..=&1.0).contains(&val) {
+                            Ok(*val)
+                        } else {
+                            Err(ShellError::GenericError {
+                                error: "Incorrect value for quantile".into(),
+                                msg: "value should be between 0 and 1".into(),
+                                span: Some(span),
+                                help: None,
+                                inner: vec![],
+                            })
+                        }
+                    }
+                    Value::Error { error, .. } => Err(*error.clone()),
+                    _ => Err(ShellError::GenericError {
+                        error: "Incorrect value for quantile".into(),
+                        msg: "value should be a float".into(),
+                        span: Some(span),
+                        help: None,
+                        inner: vec![],
+                    }),
+                }
+            })
+            .collect::<Result<Vec<f64>, ShellError>>()
+    });
+
+    let quantiles = match quantiles {
+        Some(quantiles) => quantiles?,
+        None => vec![0.25, 0.50, 0.75],
+    };
+
+    let mut quantiles_labels = quantiles
+        .iter()
+        .map(|q| Some(format!("{}%", q * 100.0)))
+        .collect::<Vec<Option<String>>>();
+    let mut labels = vec![
+        Some("count".to_string()),
+        Some("sum".to_string()),
+        Some("mean".to_string()),
+        Some("median".to_string()),
+        Some("std".to_string()),
+        Some("min".to_string()),
+    ];
+    labels.append(&mut quantiles_labels);
+    labels.push(Some("max".to_string()));
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let names = ChunkedArray::<StringType>::from_slice_options("descriptor", &labels).into_series();
+
+    let head = std::iter::once(names);
+
+    let tail = df
+        .as_ref()
+        .get_columns()
+        .iter()
+        .filter(|col| !matches!(col.dtype(), &DataType::Object("object", _)))
+        .map(|col| {
+            let count = col.len() as f64;
+
+            let sum = col.sum_as_series().ok().and_then(|series| {
+                series
+                    .cast(&DataType::Float64)
+                    .ok()
+                    .and_then(|ca| match ca.get(0) {
+                        Ok(AnyValue::Float64(v)) => Some(v),
+                        _ => None,
+                    })
+            });
+
+            let mean = match col.mean_as_series().get(0) {
+                Ok(AnyValue::Float64(v)) => Some(v),
+                _ => None,
+            };
+
+            let median = match col.median_as_series() {
+                Ok(v) => match v.get(0) {
+                    Ok(AnyValue::Float64(v)) => Some(v),
+                    _ => None,
+                },
+                _ => None,
+            };
+
+            let std = match col.std_as_series(0) {
+                Ok(v) => match v.get(0) {
+                    Ok(AnyValue::Float64(v)) => Some(v),
+                    _ => None,
+                },
+                _ => None,
+            };
+
+            let min = col.min_as_series().ok().and_then(|series| {
+                series
+                    .cast(&DataType::Float64)
+                    .ok()
+                    .and_then(|ca| match ca.get(0) {
+                        Ok(AnyValue::Float64(v)) => Some(v),
+                        _ => None,
+                    })
+            });
+
+            let mut quantiles = quantiles
+                .clone()
+                .into_iter()
+                .map(|q| {
+                    col.quantile_as_series(q, QuantileInterpolOptions::default())
+                        .ok()
+                        .and_then(|ca| ca.cast(&DataType::Float64).ok())
+                        .and_then(|ca| match ca.get(0) {
+                            Ok(AnyValue::Float64(v)) => Some(v),
+                            _ => None,
+                        })
+                })
+                .collect::<Vec<Option<f64>>>();
+
+            let max = col.max_as_series().ok().and_then(|series| {
+                series
+                    .cast(&DataType::Float64)
+                    .ok()
+                    .and_then(|ca| match ca.get(0) {
+                        Ok(AnyValue::Float64(v)) => Some(v),
+                        _ => None,
+                    })
+            });
+
+            let mut descriptors = vec![Some(count), sum, mean, median, std, min];
+            descriptors.append(&mut quantiles);
+            descriptors.push(max);
+
+            let name = format!("{} ({})", col.name(), col.dtype());
+            ChunkedArray::<Float64Type>::from_slice_options(&name, &descriptors).into_series()
+        });
+
+    let res = head.chain(tail).collect::<Vec<Series>>();
+
+    let polars_df = DataFrame::new(res).map_err(|e| ShellError::GenericError {
+        error: "Dataframe Error".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let df = NuDataFrame::new(df.from_lazy, polars_df);
+
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Summary)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/take.rs b/crates/nu_plugin_polars/src/dataframe/eager/take.rs
new file mode 100644
index 0000000000..87601080d5
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/take.rs
@@ -0,0 +1,162 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::DataType;
+
+use crate::{
+    dataframe::values::Column,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct TakeDF;
+
+impl PluginCommand for TakeDF {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars take"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates new dataframe using the given indices."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "indices",
+                SyntaxShape::Any,
+                "list of indices used to take data",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Takes selected rows from dataframe",
+                example: r#"let df = ([[a b]; [4 1] [5 2] [4 3]] | polars into-df);
+    let indices = ([0 2] | polars into-df);
+    $df | polars take $indices"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(4), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Takes selected rows from series",
+                example: r#"let series = ([4 1 5 2 4 3] | polars into-df);
+    let indices = ([0 2] | polars into-df);
+    $series | polars take $indices"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0".to_string(),
+                            vec![Value::test_int(4), Value::test_int(5)],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let index_value: Value = call.req(0)?;
+    let index_span = index_value.span();
+    let index = NuDataFrame::try_from_value(plugin, &index_value)?.as_series(index_span)?;
+
+    let casted = match index.dtype() {
+        DataType::UInt32 | DataType::UInt64 | DataType::Int32 | DataType::Int64 => index
+            .cast(&DataType::UInt32)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error casting index list".into(),
+                msg: e.to_string(),
+                span: Some(index_span),
+                help: None,
+                inner: vec![],
+            }),
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect type".into(),
+            msg: "Series with incorrect type".into(),
+            span: Some(call.head),
+            help: Some("Consider using a Series with type int type".into()),
+            inner: vec![],
+        }),
+    }?;
+
+    let indices = casted.u32().map_err(|e| ShellError::GenericError {
+        error: "Error casting index list".into(),
+        msg: e.to_string(),
+        span: Some(index_span),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let polars_df = df
+        .to_polars()
+        .take(indices)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error taking values".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let df = NuDataFrame::new(df.from_lazy, polars_df);
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&TakeDF)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/to_arrow.rs b/crates/nu_plugin_polars/src/dataframe/eager/to_arrow.rs
new file mode 100644
index 0000000000..fe09b27851
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/to_arrow.rs
@@ -0,0 +1,87 @@
+use std::{fs::File, path::PathBuf};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Spanned, SyntaxShape,
+    Type, Value,
+};
+use polars::prelude::{IpcWriter, SerWriter};
+
+use crate::PolarsPlugin;
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct ToArrow;
+
+impl PluginCommand for ToArrow {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars to-arrow"
+    }
+
+    fn usage(&self) -> &str {
+        "Saves dataframe to arrow file."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("file", SyntaxShape::Filepath, "file path to save dataframe")
+            .input_output_type(Type::Custom("dataframe".into()), Type::Any)
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Saves dataframe to arrow file",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars to-arrow test.arrow",
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        _engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, call, input).map_err(|e| e.into())
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let file_name: Spanned<PathBuf> = call.req(0)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let mut file = File::create(&file_name.item).map_err(|e| ShellError::GenericError {
+        error: "Error with file name".into(),
+        msg: e.to_string(),
+        span: Some(file_name.span),
+        help: None,
+        inner: vec![],
+    })?;
+
+    IpcWriter::new(&mut file)
+        .finish(&mut df.to_polars())
+        .map_err(|e| ShellError::GenericError {
+            error: "Error saving file".into(),
+            msg: e.to_string(),
+            span: Some(file_name.span),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let file_value = Value::string(format!("saved {:?}", &file_name.item), file_name.span);
+
+    Ok(PipelineData::Value(
+        Value::list(vec![file_value], call.head),
+        None,
+    ))
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/to_avro.rs b/crates/nu_plugin_polars/src/dataframe/eager/to_avro.rs
new file mode 100644
index 0000000000..aec58893ad
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/to_avro.rs
@@ -0,0 +1,117 @@
+use std::{fs::File, path::PathBuf};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Spanned, SyntaxShape,
+    Type, Value,
+};
+use polars_io::avro::{AvroCompression, AvroWriter};
+use polars_io::SerWriter;
+
+use crate::PolarsPlugin;
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct ToAvro;
+
+impl PluginCommand for ToAvro {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars to-avro"
+    }
+
+    fn usage(&self) -> &str {
+        "Saves dataframe to avro file."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .named(
+                "compression",
+                SyntaxShape::String,
+                "use compression, supports deflate or snappy",
+                Some('c'),
+            )
+            .required("file", SyntaxShape::Filepath, "file path to save dataframe")
+            .input_output_type(Type::Custom("dataframe".into()), Type::Any)
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Saves dataframe to avro file",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars to-avro test.avro",
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn get_compression(call: &EvaluatedCall) -> Result<Option<AvroCompression>, ShellError> {
+    if let Some((compression, span)) = call
+        .get_flag_value("compression")
+        .map(|e| e.as_str().map(|s| (s.to_owned(), e.span())))
+        .transpose()?
+    {
+        match compression.as_ref() {
+            "snappy" => Ok(Some(AvroCompression::Snappy)),
+            "deflate" => Ok(Some(AvroCompression::Deflate)),
+            _ => Err(ShellError::IncorrectValue {
+                msg: "compression must be one of deflate or snappy".to_string(),
+                val_span: span,
+                call_span: span,
+            }),
+        }
+    } else {
+        Ok(None)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    _engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let file_name: Spanned<PathBuf> = call.req(0)?;
+    let compression = get_compression(call)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let file = File::create(&file_name.item).map_err(|e| ShellError::GenericError {
+        error: "Error with file name".into(),
+        msg: e.to_string(),
+        span: Some(file_name.span),
+        help: None,
+        inner: vec![],
+    })?;
+
+    AvroWriter::new(file)
+        .with_compression(compression)
+        .finish(&mut df.to_polars())
+        .map_err(|e| ShellError::GenericError {
+            error: "Error saving file".into(),
+            msg: e.to_string(),
+            span: Some(file_name.span),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let file_value = Value::string(format!("saved {:?}", &file_name.item), file_name.span);
+
+    Ok(PipelineData::Value(
+        Value::list(vec![file_value], call.head),
+        None,
+    ))
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/to_csv.rs b/crates/nu_plugin_polars/src/dataframe/eager/to_csv.rs
new file mode 100644
index 0000000000..460bda79c8
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/to_csv.rs
@@ -0,0 +1,133 @@
+use std::{fs::File, path::PathBuf};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Spanned, SyntaxShape,
+    Type, Value,
+};
+use polars::prelude::{CsvWriter, SerWriter};
+
+use crate::PolarsPlugin;
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct ToCSV;
+
+impl PluginCommand for ToCSV {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars to-csv"
+    }
+
+    fn usage(&self) -> &str {
+        "Saves dataframe to CSV file."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("file", SyntaxShape::Filepath, "file path to save dataframe")
+            .named(
+                "delimiter",
+                SyntaxShape::String,
+                "file delimiter character",
+                Some('d'),
+            )
+            .switch("no-header", "Indicates if file doesn't have header", None)
+            .input_output_type(Type::Custom("dataframe".into()), Type::Any)
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Saves dataframe to CSV file",
+                example: "[[a b]; [1 2] [3 4]] | dfr into-df | dfr to-csv test.csv",
+                result: None,
+            },
+            Example {
+                description: "Saves dataframe to CSV file using other delimiter",
+                example: "[[a b]; [1 2] [3 4]] | dfr into-df | dfr to-csv test.csv --delimiter '|'",
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        _engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, call, input).map_err(|e| e.into())
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let file_name: Spanned<PathBuf> = call.req(0)?;
+    let delimiter: Option<Spanned<String>> = call.get_flag("delimiter")?;
+    let no_header: bool = call.has_flag("no-header")?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let mut file = File::create(&file_name.item).map_err(|e| ShellError::GenericError {
+        error: "Error with file name".into(),
+        msg: e.to_string(),
+        span: Some(file_name.span),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let writer = CsvWriter::new(&mut file);
+
+    let writer = if no_header {
+        writer.include_header(false)
+    } else {
+        writer.include_header(true)
+    };
+
+    let mut writer = match delimiter {
+        None => writer,
+        Some(d) => {
+            if d.item.len() != 1 {
+                return Err(ShellError::GenericError {
+                    error: "Incorrect delimiter".into(),
+                    msg: "Delimiter has to be one char".into(),
+                    span: Some(d.span),
+                    help: None,
+                    inner: vec![],
+                });
+            } else {
+                let delimiter = match d.item.chars().next() {
+                    Some(d) => d as u8,
+                    None => unreachable!(),
+                };
+
+                writer.with_separator(delimiter)
+            }
+        }
+    };
+
+    writer
+        .finish(&mut df.to_polars())
+        .map_err(|e| ShellError::GenericError {
+            error: "Error writing to file".into(),
+            msg: e.to_string(),
+            span: Some(file_name.span),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let file_value = Value::string(format!("saved {:?}", &file_name.item), file_name.span);
+
+    Ok(PipelineData::Value(
+        Value::list(vec![file_value], call.head),
+        None,
+    ))
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/to_df.rs b/crates/nu_plugin_polars/src/dataframe/eager/to_df.rs
new file mode 100644
index 0000000000..758feacf70
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/to_df.rs
@@ -0,0 +1,201 @@
+use crate::{
+    dataframe::values::NuSchema,
+    values::{to_pipeline_data, Column, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
+};
+use polars::{
+    prelude::{AnyValue, DataType, Field, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct ToDataFrame;
+
+impl PluginCommand for ToDataFrame {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars into-df"
+    }
+
+    fn usage(&self) -> &str {
+        "Converts a list, table or record into a dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .named(
+                "schema",
+                SyntaxShape::Record(vec![]),
+                r#"Polars Schema in format [{name: str}]. CSV, JSON, and JSONL files"#,
+                Some('s'),
+            )
+            .input_output_type(Type::Any, Type::Custom("dataframe".into()))
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Takes a dictionary and creates a dataframe",
+                example: "[[a b];[1 2] [3 4]] | polars into-df",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Takes a list of tables and creates a dataframe",
+                example: "[[1 2 a] [3 4 b] [5 6 c]] | polars into-df",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "0".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3), Value::test_int(5)],
+                            ),
+                            Column::new(
+                                "1".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4), Value::test_int(6)],
+                            ),
+                            Column::new(
+                                "2".to_string(),
+                                vec![
+                                    Value::test_string("a"),
+                                    Value::test_string("b"),
+                                    Value::test_string("c"),
+                                ],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Takes a list and creates a dataframe",
+                example: "[a b c] | polars into-df",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0".to_string(),
+                            vec![
+                                Value::test_string("a"),
+                                Value::test_string("b"),
+                                Value::test_string("c"),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Takes a list of booleans and creates a dataframe",
+                example: "[true true false] | polars into-df",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0".to_string(),
+                            vec![
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(false),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Convert to a dataframe and provide a schema",
+                example: "{a: 1, b: {a: [1 2 3]}, c: [a b c]}| polars into-df -s {a: u8, b: {a: list<u64>}, c: list<str>}",
+                result: Some(
+                    NuDataFrame::try_from_series_vec(vec![
+                        Series::new("a", &[1u8]),
+                        {
+                            let dtype = DataType::Struct(vec![Field::new("a", DataType::List(Box::new(DataType::UInt64)))]);
+                            let vals = vec![AnyValue::StructOwned(
+                                Box::new((vec![AnyValue::List(Series::new("a", &[1u64, 2, 3]))], vec![Field::new("a", DataType::String)]))); 1];
+                            Series::from_any_values_and_dtype("b", &vals, &dtype, false)
+                                .expect("Struct series should not fail")
+                        },
+                        {
+                            let dtype = DataType::List(Box::new(DataType::String));
+                            let vals = vec![AnyValue::List(Series::new("c", &["a", "b", "c"]))];
+                            Series::from_any_values_and_dtype("c", &vals, &dtype, false)
+                                .expect("List series should not fail")
+                        }
+                    ], Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Convert to a dataframe and provide a schema that adds a new column",
+                example: r#"[[a b]; [1 "foo"] [2 "bar"]] | polars into-df -s {a: u8, b:str, c:i64} | polars fill-null 3"#,
+                result: Some(NuDataFrame::try_from_series_vec(vec![
+                        Series::new("a", [1u8, 2]),
+                        Series::new("b", ["foo", "bar"]),
+                        Series::new("c", [3i64, 3]),
+                    ], Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            }
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let maybe_schema = call
+            .get_flag("schema")?
+            .map(|schema| NuSchema::try_from(&schema))
+            .transpose()?;
+
+        let df = NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?;
+        to_pipeline_data(plugin, engine, call.head, df).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+    use nu_protocol::ShellError;
+
+    #[test]
+    fn test_into_df() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ToDataFrame)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/to_json_lines.rs b/crates/nu_plugin_polars/src/dataframe/eager/to_json_lines.rs
new file mode 100644
index 0000000000..fa313db895
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/to_json_lines.rs
@@ -0,0 +1,89 @@
+use std::{fs::File, io::BufWriter, path::PathBuf};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Spanned, SyntaxShape,
+    Type, Value,
+};
+use polars::prelude::{JsonWriter, SerWriter};
+
+use crate::PolarsPlugin;
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct ToJsonLines;
+
+impl PluginCommand for ToJsonLines {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars to-jsonl"
+    }
+
+    fn usage(&self) -> &str {
+        "Saves dataframe to a JSON lines file."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("file", SyntaxShape::Filepath, "file path to save dataframe")
+            .input_output_type(Type::Custom("dataframe".into()), Type::Any)
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Saves dataframe to JSON lines file",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars to-jsonl test.jsonl",
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    _engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let file_name: Spanned<PathBuf> = call.req(0)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let file = File::create(&file_name.item).map_err(|e| ShellError::GenericError {
+        error: "Error with file name".into(),
+        msg: e.to_string(),
+        span: Some(file_name.span),
+        help: None,
+        inner: vec![],
+    })?;
+    let buf_writer = BufWriter::new(file);
+
+    JsonWriter::new(buf_writer)
+        .finish(&mut df.to_polars())
+        .map_err(|e| ShellError::GenericError {
+            error: "Error saving file".into(),
+            msg: e.to_string(),
+            span: Some(file_name.span),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let file_value = Value::string(format!("saved {:?}", &file_name.item), file_name.span);
+
+    Ok(PipelineData::Value(
+        Value::list(vec![file_value], call.head),
+        None,
+    ))
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/to_nu.rs b/crates/nu_plugin_polars/src/dataframe/eager/to_nu.rs
new file mode 100644
index 0000000000..832396b139
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/to_nu.rs
@@ -0,0 +1,144 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    record, Category, Example, LabeledError, PipelineData, ShellError, Signature, Span,
+    SyntaxShape, Type, Value,
+};
+
+use crate::{dataframe::values::NuExpression, values::CustomValueSupport, PolarsPlugin};
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct ToNu;
+
+impl PluginCommand for ToNu {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars into-nu"
+    }
+
+    fn usage(&self) -> &str {
+        "Converts a dataframe or an expression into into nushell value for access and exploration."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .named(
+                "rows",
+                SyntaxShape::Number,
+                "number of rows to be shown",
+                Some('n'),
+            )
+            .switch("tail", "shows tail rows", Some('t'))
+            .input_output_types(vec![
+                (Type::Custom("expression".into()), Type::Any),
+                (Type::Custom("dataframe".into()), Type::Table(vec![])),
+            ])
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        let rec_1 = Value::test_record(record! {
+            "index" => Value::test_int(0),
+            "a" =>     Value::test_int(1),
+            "b" =>     Value::test_int(2),
+        });
+        let rec_2 = Value::test_record(record! {
+            "index" => Value::test_int(1),
+            "a" =>     Value::test_int(3),
+            "b" =>     Value::test_int(4),
+        });
+        let rec_3 = Value::test_record(record! {
+            "index" => Value::test_int(2),
+            "a" =>     Value::test_int(3),
+            "b" =>     Value::test_int(4),
+        });
+
+        vec![
+            Example {
+                description: "Shows head rows from dataframe",
+                example: "[[a b]; [1 2] [3 4]] | polars into-df | polars into-nu",
+                result: Some(Value::list(vec![rec_1, rec_2], Span::test_data())),
+            },
+            Example {
+                description: "Shows tail rows from dataframe",
+                example:
+                    "[[a b]; [1 2] [5 6] [3 4]] | polars into-df | polars into-nu --tail --rows 1",
+                result: Some(Value::list(vec![rec_3], Span::test_data())),
+            },
+            Example {
+                description: "Convert a col expression into a nushell value",
+                example: "polars col a | polars into-nu",
+                result: Some(Value::test_record(record! {
+                    "expr" =>  Value::test_string("column"),
+                    "value" => Value::test_string("a"),
+                })),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        _engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        if NuDataFrame::can_downcast(&value) {
+            dataframe_command(plugin, call, value)
+        } else {
+            expression_command(plugin, call, value)
+        }
+        .map_err(|e| e.into())
+    }
+}
+
+fn dataframe_command(
+    plugin: &PolarsPlugin,
+    call: &EvaluatedCall,
+    input: Value,
+) -> Result<PipelineData, ShellError> {
+    let rows: Option<usize> = call.get_flag("rows")?;
+    let tail: bool = call.has_flag("tail")?;
+
+    let df = NuDataFrame::try_from_value(plugin, &input)?;
+
+    let values = if tail {
+        df.tail(rows, call.head)?
+    } else {
+        // if rows is specified, return those rows, otherwise return everything
+        if rows.is_some() {
+            df.head(rows, call.head)?
+        } else {
+            df.head(Some(df.height()), call.head)?
+        }
+    };
+
+    let value = Value::list(values, call.head);
+
+    Ok(PipelineData::Value(value, None))
+}
+
+fn expression_command(
+    plugin: &PolarsPlugin,
+    call: &EvaluatedCall,
+    input: Value,
+) -> Result<PipelineData, ShellError> {
+    let expr = NuExpression::try_from_value(plugin, &input)?;
+    let value = expr.to_value(call.head)?;
+
+    Ok(PipelineData::Value(value, None))
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ToNu)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/to_parquet.rs b/crates/nu_plugin_polars/src/dataframe/eager/to_parquet.rs
new file mode 100644
index 0000000000..571d5e040d
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/to_parquet.rs
@@ -0,0 +1,87 @@
+use std::{fs::File, path::PathBuf};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Spanned, SyntaxShape,
+    Type, Value,
+};
+use polars::prelude::ParquetWriter;
+
+use crate::PolarsPlugin;
+
+use super::super::values::NuDataFrame;
+
+#[derive(Clone)]
+pub struct ToParquet;
+
+impl PluginCommand for ToParquet {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars to-parquet"
+    }
+
+    fn usage(&self) -> &str {
+        "Saves dataframe to parquet file."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("file", SyntaxShape::Filepath, "file path to save dataframe")
+            .input_output_type(Type::Custom("dataframe".into()), Type::Any)
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Saves dataframe to parquet file",
+            example: "[[a b]; [1 2] [3 4]] | polars into-df | polars to-parquet test.parquet",
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        _engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let file_name: Spanned<PathBuf> = call.req(0)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let file = File::create(&file_name.item).map_err(|e| ShellError::GenericError {
+        error: "Error with file name".into(),
+        msg: e.to_string(),
+        span: Some(file_name.span),
+        help: None,
+        inner: vec![],
+    })?;
+    let mut polars_df = df.to_polars();
+    ParquetWriter::new(file)
+        .finish(&mut polars_df)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error saving file".into(),
+            msg: e.to_string(),
+            span: Some(file_name.span),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let file_value = Value::string(format!("saved {:?}", &file_name.item), file_name.span);
+
+    Ok(PipelineData::Value(
+        Value::list(vec![file_value], call.head),
+        None,
+    ))
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/eager/with_column.rs b/crates/nu_plugin_polars/src/dataframe/eager/with_column.rs
new file mode 100644
index 0000000000..049d0beeb7
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/eager/with_column.rs
@@ -0,0 +1,195 @@
+use super::super::values::{Column, NuDataFrame};
+use crate::{
+    dataframe::values::{NuExpression, NuLazyFrame},
+    values::{to_pipeline_data, CustomValueSupport, PolarsPluginObject},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct WithColumn;
+
+impl PluginCommand for WithColumn {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars with-column"
+    }
+
+    fn usage(&self) -> &str {
+        "Adds a series to the dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .named("name", SyntaxShape::String, "new column name", Some('n'))
+            .rest(
+                "series or expressions",
+                SyntaxShape::Any,
+                "series to be added or expressions used to define the new columns",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe or lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Adds a series to the dataframe",
+                example: r#"[[a b]; [1 2] [3 4]]
+    | polars into-df
+    | polars with-column ([5 6] | polars into-df) --name c"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "c".to_string(),
+                                vec![Value::test_int(5), Value::test_int(6)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Adds a series to the dataframe",
+                example: r#"[[a b]; [1 2] [3 4]]
+    | polars into-lazy
+    | polars with-column [
+        ((polars col a) * 2 | polars as "c")
+        ((polars col a) * 3 | polars as "d")
+      ]
+    | polars collect"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "c".to_string(),
+                                vec![Value::test_int(2), Value::test_int(6)],
+                            ),
+                            Column::new(
+                                "d".to_string(),
+                                vec![Value::test_int(3), Value::test_int(9)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command_eager(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => command_lazy(plugin, engine, call, lazy),
+            _ => Err(ShellError::CantConvert {
+                to_type: "lazy or eager dataframe".into(),
+                from_type: value.get_type().to_string(),
+                span: value.span(),
+                help: None,
+            }),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command_eager(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let new_column: Value = call.req(0)?;
+    let column_span = new_column.span();
+
+    if NuExpression::can_downcast(&new_column) {
+        let vals: Vec<Value> = call.rest(0)?;
+        let value = Value::list(vals, call.head);
+        let expressions = NuExpression::extract_exprs(plugin, value)?;
+        let lazy = NuLazyFrame::new(true, df.lazy().to_polars().with_columns(&expressions));
+        let df = lazy.collect(call.head)?;
+        to_pipeline_data(plugin, engine, call.head, df)
+    } else {
+        let mut other = NuDataFrame::try_from_value(plugin, &new_column)?.as_series(column_span)?;
+
+        let name = match call.get_flag::<String>("name")? {
+            Some(name) => name,
+            None => other.name().to_string(),
+        };
+
+        let series = other.rename(&name).clone();
+
+        let mut polars_df = df.to_polars();
+        polars_df
+            .with_column(series)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error adding column to dataframe".into(),
+                msg: e.to_string(),
+                span: Some(column_span),
+                help: None,
+                inner: vec![],
+            })?;
+
+        let df = NuDataFrame::new(df.from_lazy, polars_df);
+        to_pipeline_data(plugin, engine, call.head, df)
+    }
+}
+
+fn command_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let vals: Vec<Value> = call.rest(0)?;
+    let value = Value::list(vals, call.head);
+    let expressions = NuExpression::extract_exprs(plugin, value)?;
+    let lazy: NuLazyFrame = lazy.to_polars().with_columns(&expressions).into();
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&WithColumn)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/alias.rs b/crates/nu_plugin_polars/src/dataframe/expressions/alias.rs
new file mode 100644
index 0000000000..7d9b851997
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/alias.rs
@@ -0,0 +1,88 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::NuExpression;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    record, Category, Example, LabeledError, PipelineData, Signature, SyntaxShape, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct ExprAlias;
+
+impl PluginCommand for ExprAlias {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars as"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates an alias expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "Alias name",
+                SyntaxShape::String,
+                "Alias name for the expression",
+            )
+            .input_output_type(
+                Type::Custom("expression".into()),
+                Type::Custom("expression".into()),
+            )
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Creates and alias expression",
+            example: "polars col a | polars as new_a | polars into-nu",
+            result: {
+                let record = Value::test_record(record! {
+                    "expr" =>  Value::test_record(record! {
+                        "expr" =>  Value::test_string("column"),
+                        "value" => Value::test_string("a"),
+                    }),
+                    "alias" => Value::test_string("new_a"),
+                });
+
+                Some(record)
+            },
+        }]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["aka", "abbr", "otherwise"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let alias: String = call.req(0)?;
+
+        let expr = NuExpression::try_from_pipeline(plugin, input, call.head)?;
+        let expr: NuExpression = expr.to_polars().alias(alias.as_str()).into();
+
+        to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&ExprAlias)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/arg_where.rs b/crates/nu_plugin_polars/src/dataframe/expressions/arg_where.rs
new file mode 100644
index 0000000000..924c0472bc
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/arg_where.rs
@@ -0,0 +1,79 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
+};
+use polars::prelude::arg_where;
+
+#[derive(Clone)]
+pub struct ExprArgWhere;
+
+impl PluginCommand for ExprArgWhere {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars arg-where"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates an expression that returns the arguments where expression is true."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("column name", SyntaxShape::Any, "Expression to evaluate")
+            .input_output_type(Type::Any, Type::Custom("expression".into()))
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Return a dataframe where the value match the expression",
+            example: "let df = ([[a b]; [one 1] [two 2] [three 3]] | polars into-df);
+    $df | polars select (polars arg-where ((polars col b) >= 2) | polars as b_arg)",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "b_arg".to_string(),
+                        vec![Value::test_int(1), Value::test_int(2)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["condition", "match", "if"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        _input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value: Value = call.req(0)?;
+        let expr = NuExpression::try_from_value(plugin, &value)?;
+        let expr: NuExpression = arg_where(expr.to_polars()).into();
+        to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&ExprArgWhere)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/col.rs b/crates/nu_plugin_polars/src/dataframe/expressions/col.rs
new file mode 100644
index 0000000000..536a38fce5
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/col.rs
@@ -0,0 +1,70 @@
+use crate::{dataframe::values::NuExpression, values::to_pipeline_data, PolarsPlugin};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    record, Category, Example, LabeledError, PipelineData, Signature, SyntaxShape, Type, Value,
+};
+use polars::prelude::col;
+
+#[derive(Clone)]
+pub struct ExprCol;
+
+impl PluginCommand for ExprCol {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars col"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates a named column expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "column name",
+                SyntaxShape::String,
+                "Name of column to be used",
+            )
+            .input_output_type(Type::Any, Type::Custom("expression".into()))
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Creates a named column expression and converts it to a nu object",
+            example: "polars col a | polars into-nu",
+            result: Some(Value::test_record(record! {
+                "expr" =>  Value::test_string("column"),
+                "value" => Value::test_string("a"),
+            })),
+        }]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["create"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        _input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let name: String = call.req(0)?;
+        let expr: NuExpression = col(name.as_str()).into();
+        to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&ExprCol)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/concat_str.rs b/crates/nu_plugin_polars/src/dataframe/expressions/concat_str.rs
new file mode 100644
index 0000000000..818e9f7e31
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/concat_str.rs
@@ -0,0 +1,109 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
+};
+use polars::prelude::concat_str;
+
+#[derive(Clone)]
+pub struct ExprConcatStr;
+
+impl PluginCommand for ExprConcatStr {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars concat-str"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates a concat string expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "separator",
+                SyntaxShape::String,
+                "Separator used during the concatenation",
+            )
+            .required(
+                "concat expressions",
+                SyntaxShape::List(Box::new(SyntaxShape::Any)),
+                "Expression(s) that define the string concatenation",
+            )
+            .input_output_type(Type::Any, Type::Custom("expression".into()))
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Creates a concat string expression",
+            example: r#"let df = ([[a b c]; [one two 1] [three four 2]] | polars into-df);
+    $df | polars with-column ((polars concat-str "-" [(polars col a) (polars col b) ((polars col c) * 2)]) | polars as concat)"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_string("one"), Value::test_string("three")],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_string("two"), Value::test_string("four")],
+                        ),
+                        Column::new(
+                            "c".to_string(),
+                            vec![Value::test_int(1), Value::test_int(2)],
+                        ),
+                        Column::new(
+                            "concat".to_string(),
+                            vec![
+                                Value::test_string("one-two-2"),
+                                Value::test_string("three-four-4"),
+                            ],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["join", "connect", "update"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        _input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let separator: String = call.req(0)?;
+        let value: Value = call.req(1)?;
+
+        let expressions = NuExpression::extract_exprs(plugin, value)?;
+        let expr: NuExpression = concat_str(expressions, &separator, false).into();
+
+        to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&ExprConcatStr)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/datepart.rs b/crates/nu_plugin_polars/src/dataframe/expressions/datepart.rs
new file mode 100644
index 0000000000..bec32ebbfb
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/datepart.rs
@@ -0,0 +1,165 @@
+use super::super::values::NuExpression;
+
+use crate::{
+    dataframe::values::{Column, NuDataFrame},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use chrono::{DateTime, FixedOffset};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Spanned,
+    SyntaxShape, Type, Value,
+};
+use polars::{
+    datatypes::{DataType, TimeUnit},
+    prelude::NamedFrom,
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct ExprDatePart;
+
+impl PluginCommand for ExprDatePart {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars datepart"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates an expression for capturing the specified datepart in a column."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "Datepart name",
+                SyntaxShape::String,
+                "Part of the date to capture.  Possible values are year, quarter, month, week, weekday, day, hour, minute, second, millisecond, microsecond, nanosecond",
+            )
+            .input_output_type(
+                Type::Custom("expression".into()),
+                Type::Custom("expression".into()),
+            )
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        let dt = DateTime::<FixedOffset>::parse_from_str(
+            "2021-12-30T01:02:03.123456789 +0000",
+            "%Y-%m-%dT%H:%M:%S.%9f %z",
+        )
+        .expect("date calculation should not fail in test");
+        vec![
+            Example {
+                description: "Creates an expression to capture the year date part",
+                example: r#"[["2021-12-30T01:02:03.123456789"]] | polars into-df | polars as-datetime "%Y-%m-%dT%H:%M:%S.%9f" | polars with-column [(polars col datetime | polars datepart year | polars as datetime_year )]"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new("datetime".to_string(), vec![Value::test_date(dt)]),
+                            Column::new("datetime_year".to_string(), vec![Value::test_int(2021)]),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates an expression to capture multiple date parts",
+                example: r#"[["2021-12-30T01:02:03.123456789"]] | polars into-df | polars as-datetime "%Y-%m-%dT%H:%M:%S.%9f" |
+                polars with-column [ (polars col datetime | polars datepart year | polars as datetime_year ),
+                (polars col datetime | polars datepart month | polars as datetime_month ),
+                (polars col datetime | polars datepart day | polars as datetime_day ),
+                (polars col datetime | polars datepart hour | polars as datetime_hour ),
+                (polars col datetime | polars datepart minute | polars as datetime_minute ),
+                (polars col datetime | polars datepart second | polars as datetime_second ),
+                (polars col datetime | polars datepart nanosecond | polars as datetime_ns ) ]"#,
+                result: Some(
+                    NuDataFrame::try_from_series_vec(
+                        vec![
+                            Series::new("datetime", &[dt.timestamp_nanos_opt()])
+                                .cast(&DataType::Datetime(TimeUnit::Nanoseconds, None))
+                                .expect("Error casting to datetime type"),
+                            Series::new("datetime_year", &[2021_i64]), // i32 was coerced to i64
+                            Series::new("datetime_month", &[12_i8]),
+                            Series::new("datetime_day", &[30_i8]),
+                            Series::new("datetime_hour", &[1_i8]),
+                            Series::new("datetime_minute", &[2_i8]),
+                            Series::new("datetime_second", &[3_i8]),
+                            Series::new("datetime_ns", &[123456789_i64]), // i32 was coerced to i64
+                        ],
+                        Span::test_data(),
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec![
+            "year",
+            "month",
+            "week",
+            "weekday",
+            "quarter",
+            "day",
+            "hour",
+            "minute",
+            "second",
+            "millisecond",
+            "microsecond",
+            "nanosecond",
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let part: Spanned<String> = call.req(0)?;
+
+        let expr = NuExpression::try_from_pipeline(plugin, input, call.head)?;
+        let expr_dt = expr.to_polars().dt();
+        let expr: NuExpression  = match part.item.as_str() {
+            "year" => expr_dt.year(),
+            "quarter" => expr_dt.quarter(),
+            "month" => expr_dt.month(),
+            "week" => expr_dt.week(),
+            "day" => expr_dt.day(),
+            "hour" => expr_dt.hour(),
+            "minute" => expr_dt.minute(),
+            "second" => expr_dt.second(),
+            "millisecond" => expr_dt.millisecond(),
+            "microsecond" => expr_dt.microsecond(),
+            "nanosecond" => expr_dt.nanosecond(),
+            _ => {
+                return Err(LabeledError::from(ShellError::UnsupportedInput {
+                    msg: format!("{} is not a valid datepart, expected one of year, month, day, hour, minute, second, millisecond, microsecond, nanosecond", part.item),
+                    input: "value originates from here".to_string(),
+                    msg_span: call.head,
+                    input_span: part.span,
+                }))
+            }
+        }.into();
+        to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ExprDatePart)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/expressions_macro.rs b/crates/nu_plugin_polars/src/dataframe/expressions/expressions_macro.rs
new file mode 100644
index 0000000000..7f53409450
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/expressions_macro.rs
@@ -0,0 +1,645 @@
+/// Definition of multiple Expression commands using a macro rule
+/// All of these expressions have an identical body and only require
+/// to have a change in the name, description and expression function
+use crate::dataframe::values::{Column, NuDataFrame, NuExpression, NuLazyFrame};
+use crate::values::{to_pipeline_data, CustomValueSupport};
+use crate::PolarsPlugin;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+// The structs defined in this file are structs that form part of other commands
+// since they share a similar name
+macro_rules! expr_command {
+    ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident, $test: ident) => {
+        #[derive(Clone)]
+        pub struct $command;
+
+        impl PluginCommand for $command {
+            type Plugin = PolarsPlugin;
+
+            fn name(&self) -> &str {
+                $name
+            }
+
+            fn usage(&self) -> &str {
+                $desc
+            }
+
+            fn signature(&self) -> Signature {
+                Signature::build(self.name())
+                    .usage($desc)
+                    .input_output_type(
+                        Type::Custom("expression".into()),
+                        Type::Custom("expression".into()),
+                    )
+                    .category(Category::Custom("expression".into()))
+            }
+
+            fn examples(&self) -> Vec<Example> {
+                $examples
+            }
+
+            fn run(
+                &self,
+                plugin: &Self::Plugin,
+                engine: &EngineInterface,
+                call: &EvaluatedCall,
+                input: PipelineData,
+            ) -> Result<PipelineData, LabeledError> {
+                let expr = NuExpression::try_from_pipeline(plugin, input, call.head)
+                    .map_err(LabeledError::from)?;
+                let expr: NuExpression = expr.to_polars().$func().into();
+                to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+            }
+        }
+
+        #[cfg(test)]
+        mod $test {
+            use super::*;
+            use crate::test::test_polars_plugin_command;
+
+            #[test]
+            fn test_examples() -> Result<(), ShellError> {
+                test_polars_plugin_command(&$command)
+            }
+        }
+    };
+
+    ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident, $test: ident, $ddof: expr) => {
+        #[derive(Clone)]
+        pub struct $command;
+
+        impl PluginCommand for $command {
+            type Plugin = PolarsPlugin;
+
+            fn signature(&self) -> Signature {
+                Signature::build(self.name())
+                    .usage($desc)
+                    .input_output_type(
+                        Type::Custom("expression".into()),
+                        Type::Custom("expression".into()),
+                    )
+                    .category(Category::Custom("expression".into()))
+                    .plugin_examples($examples)
+            }
+
+            fn run(
+                &self,
+                _plugin: &Self::Plugin,
+                engine: &EngineInterface,
+                call: &EvaluatedCall,
+                input: PipelineData,
+            ) -> Result<PipelineData, LabeledError> {
+                let expr = NuExpression::try_from_pipeline(input, call.head)
+                    .map_err(LabeledError::from)?;
+                let expr: NuExpression = expr.into_polars().$func($ddof).into();
+                to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+            }
+        }
+
+        #[cfg(test)]
+        mod $test {
+            use super::*;
+            use crate::test::test_polars_plugin_command;
+
+            #[test]
+            fn test_examples() -> Result<(), ShellError> {
+                test_polars_plugin_command(&$command)
+            }
+        }
+    };
+}
+
+// The structs defined in this file are structs that form part of other commands
+// since they share a similar name
+macro_rules! lazy_expr_command {
+    ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident, $test: ident) => {
+        #[derive(Clone)]
+        pub struct $command;
+
+        impl PluginCommand for $command {
+            type Plugin = PolarsPlugin;
+
+            fn name(&self) -> &str {
+                $name
+            }
+
+            fn usage(&self) -> &str {
+                $desc
+            }
+
+            fn signature(&self) -> Signature {
+                Signature::build(self.name())
+                    .usage($desc)
+                    .input_output_types(vec![
+                        (
+                            Type::Custom("expression".into()),
+                            Type::Custom("expression".into()),
+                        ),
+                        (
+                            Type::Custom("dataframe".into()),
+                            Type::Custom("dataframe".into()),
+                        ),
+                    ])
+                    .category(Category::Custom("expression".into()))
+            }
+
+            fn examples(&self) -> Vec<Example> {
+                $examples
+            }
+
+            fn run(
+                &self,
+                plugin: &Self::Plugin,
+                engine: &EngineInterface,
+                call: &EvaluatedCall,
+                input: PipelineData,
+            ) -> Result<PipelineData, LabeledError> {
+                let value = input.into_value(call.head);
+                if NuDataFrame::can_downcast(&value) || NuLazyFrame::can_downcast(&value) {
+                    let lazy = NuLazyFrame::try_from_value_coerce(plugin, &value)
+                        .map_err(LabeledError::from)?;
+                    let lazy = NuLazyFrame::new(
+                        lazy.from_eager,
+                        lazy.to_polars()
+                            .$func()
+                            .map_err(|e| ShellError::GenericError {
+                                error: "Dataframe Error".into(),
+                                msg: e.to_string(),
+                                help: None,
+                                span: None,
+                                inner: vec![],
+                            })
+                            .map_err(LabeledError::from)?,
+                    );
+                    to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+                } else {
+                    let expr =
+                        NuExpression::try_from_value(plugin, &value).map_err(LabeledError::from)?;
+                    let expr: NuExpression = expr.to_polars().$func().into();
+                    to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+                }
+            }
+        }
+
+        #[cfg(test)]
+        mod $test {
+            use super::*;
+            use crate::test::test_polars_plugin_command;
+
+            #[test]
+            fn test_examples() -> Result<(), ShellError> {
+                test_polars_plugin_command(&$command)
+            }
+        }
+    };
+
+    ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident, $test: ident, $ddof: expr) => {
+        #[derive(Clone)]
+        pub struct $command;
+
+        impl PluginCommand for $command {
+            type Plugin = PolarsPlugin;
+
+            fn name(&self) -> &str {
+                $name
+            }
+
+            fn usage(&self) -> &str {
+                $desc
+            }
+            fn signature(&self) -> Signature {
+                Signature::build(self.name())
+                    .input_output_types(vec![
+                        (
+                            Type::Custom("expression".into()),
+                            Type::Custom("expression".into()),
+                        ),
+                        (
+                            Type::Custom("dataframe".into()),
+                            Type::Custom("dataframe".into()),
+                        ),
+                    ])
+                    .category(Category::Custom("expression".into()))
+            }
+
+            fn examples(&self) -> Vec<Example> {
+                $examples
+            }
+
+            fn run(
+                &self,
+                plugin: &Self::Plugin,
+                engine: &EngineInterface,
+                call: &EvaluatedCall,
+                input: PipelineData,
+            ) -> Result<PipelineData, LabeledError> {
+                let value = input.into_value(call.head);
+                if NuDataFrame::can_downcast(&value) || NuLazyFrame::can_downcast(&value) {
+                    let lazy = NuLazyFrame::try_from_value_coerce(plugin, &value)
+                        .map_err(LabeledError::from)?;
+                    let lazy = NuLazyFrame::new(
+                        lazy.from_eager,
+                        lazy.to_polars()
+                            .$func($ddof)
+                            .map_err(|e| ShellError::GenericError {
+                                error: "Dataframe Error".into(),
+                                msg: e.to_string(),
+                                help: None,
+                                span: None,
+                                inner: vec![],
+                            })
+                            .map_err(LabeledError::from)?,
+                    );
+                    to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+                } else {
+                    let expr = NuExpression::try_from_value(plugin, &value)?;
+                    let expr: NuExpression = expr.to_polars().$func($ddof).into();
+                    to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+                }
+            }
+        }
+
+        #[cfg(test)]
+        mod $test {
+            use super::*;
+            use crate::test::test_polars_plugin_command;
+
+            #[test]
+            fn test_examples() -> Result<(), ShellError> {
+                test_polars_plugin_command(&$command)
+            }
+        }
+    };
+}
+
+// ExprList command
+// Expands to a command definition for a list expression
+expr_command!(
+    ExprList,
+    "polars implode",
+    "Aggregates a group to a Series.",
+    vec![Example {
+        description: "",
+        example: "",
+        result: None,
+    }],
+    implode,
+    test_implode
+);
+
+// ExprAggGroups command
+// Expands to a command definition for a agg groups expression
+expr_command!(
+    ExprAggGroups,
+    "polars agg-groups",
+    "Creates an agg_groups expression.",
+    vec![Example {
+        description: "",
+        example: "",
+        result: None,
+    }],
+    agg_groups,
+    test_groups
+);
+
+// ExprCount command
+// Expands to a command definition for a count expression
+expr_command!(
+    ExprCount,
+    "polars count",
+    "Creates a count expression.",
+    vec![Example {
+        description: "",
+        example: "",
+        result: None,
+    }],
+    count,
+    test_count
+);
+
+// ExprNot command
+// Expands to a command definition for a not expression
+expr_command!(
+    ExprNot,
+    "polars expr-not",
+    "Creates a not expression.",
+    vec![Example {
+        description: "Creates a not expression",
+        example: "(polars col a) > 2) | polars expr-not",
+        result: None,
+    },],
+    not,
+    test_not
+);
+
+// ExprMax command
+// Expands to a command definition for max aggregation
+lazy_expr_command!(
+    ExprMax,
+    "polars max",
+    "Creates a max expression or aggregates columns to their max value.",
+    vec![
+        Example {
+            description: "Max value from columns in a dataframe",
+            example: "[[a b]; [6 2] [1 4] [4 1]] | polars into-df | polars max",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("a".to_string(), vec![Value::test_int(6)],),
+                        Column::new("b".to_string(), vec![Value::test_int(4)],),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+        Example {
+            description: "Max aggregation for a group-by",
+            example: r#"[[a b]; [one 2] [one 4] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars max)"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_string("one"), Value::test_string("two")],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(4), Value::test_int(1)],
+                        ),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+    ],
+    max,
+    test_max
+);
+
+// ExprMin command
+// Expands to a command definition for min aggregation
+lazy_expr_command!(
+    ExprMin,
+    "polars min",
+    "Creates a min expression or aggregates columns to their min value.",
+    vec![
+        Example {
+            description: "Min value from columns in a dataframe",
+            example: "[[a b]; [6 2] [1 4] [4 1]] | polars into-df | polars min",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("a".to_string(), vec![Value::test_int(1)],),
+                        Column::new("b".to_string(), vec![Value::test_int(1)],),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+        Example {
+            description: "Min aggregation for a group-by",
+            example: r#"[[a b]; [one 2] [one 4] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars min)"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_string("one"), Value::test_string("two")],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(2), Value::test_int(1)],
+                        ),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+    ],
+    min,
+    test_min
+);
+
+// ExprSum command
+// Expands to a command definition for sum aggregation
+lazy_expr_command!(
+    ExprSum,
+    "polars sum",
+    "Creates a sum expression for an aggregation or aggregates columns to their sum value.",
+    vec![
+        Example {
+            description: "Sums all columns in a dataframe",
+            example: "[[a b]; [6 2] [1 4] [4 1]] | polars into-df | polars sum",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("a".to_string(), vec![Value::test_int(11)],),
+                        Column::new("b".to_string(), vec![Value::test_int(7)],),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+        Example {
+            description: "Sum aggregation for a group-by",
+            example: r#"[[a b]; [one 2] [one 4] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars sum)"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_string("one"), Value::test_string("two")],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(6), Value::test_int(1)],
+                        ),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+    ],
+    sum,
+    test_sum
+);
+
+// ExprMean command
+// Expands to a command definition for mean aggregation
+lazy_expr_command!(
+    ExprMean,
+    "polars mean",
+    "Creates a mean expression for an aggregation or aggregates columns to their mean value.",
+    vec![
+        Example {
+            description: "Mean value from columns in a dataframe",
+            example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars mean",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("a".to_string(), vec![Value::test_float(4.0)],),
+                        Column::new("b".to_string(), vec![Value::test_float(2.0)],),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+        Example {
+            description: "Mean aggregation for a group-by",
+            example: r#"[[a b]; [one 2] [one 4] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars mean)"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_string("one"), Value::test_string("two")],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_float(3.0), Value::test_float(1.0)],
+                        ),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+    ],
+    mean,
+    test_mean
+);
+
+// ExprStd command
+// Expands to a command definition for std aggregation
+lazy_expr_command!(
+    ExprStd,
+    "polars std",
+    "Creates a std expression for an aggregation of std value from columns in a dataframe.",
+    vec![
+        Example {
+            description: "Std value from columns in a dataframe",
+            example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars std",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("a".to_string(), vec![Value::test_float(2.0)],),
+                        Column::new("b".to_string(), vec![Value::test_float(0.0)],),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+        Example {
+            description: "Std aggregation for a group-by",
+            example: r#"[[a b]; [one 2] [one 2] [two 1] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars std)"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_string("one"), Value::test_string("two")],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_float(0.0), Value::test_float(0.0)],
+                        ),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+    ],
+    std,
+    test_std,
+    1
+);
+
+// ExprVar command
+// Expands to a command definition for var aggregation
+lazy_expr_command!(
+    ExprVar,
+    "polars var",
+    "Create a var expression for an aggregation.",
+    vec![
+        Example {
+            description:
+                "Var value from columns in a dataframe or aggregates columns to their var value",
+            example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars var",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new("a".to_string(), vec![Value::test_float(4.0)],),
+                        Column::new("b".to_string(), vec![Value::test_float(0.0)],),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+        Example {
+            description: "Var aggregation for a group-by",
+            example: r#"[[a b]; [one 2] [one 2] [two 1] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars var)"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_string("one"), Value::test_string("two")],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_float(0.0), Value::test_float(0.0)],
+                        ),
+                    ],
+                    None
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        },
+    ],
+    var,
+    test_var,
+    1
+);
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/is_in.rs b/crates/nu_plugin_polars/src/dataframe/expressions/is_in.rs
new file mode 100644
index 0000000000..4402b11adf
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/is_in.rs
@@ -0,0 +1,200 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{is_in, lit, DataType, IntoSeries};
+
+#[derive(Clone)]
+pub struct ExprIsIn;
+
+impl PluginCommand for ExprIsIn {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars is-in"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates an is-in expression or checks to see if the elements are contained in the right series"
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("list", SyntaxShape::Any, "List to check if values are in")
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Creates a is-in expression",
+                example: r#"let df = ([[a b]; [one 1] [two 2] [three 3]] | polars into-df);
+            $df | polars with-column (polars col a | polars is-in [one two] | polars as a_in)"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![
+                                    Value::test_string("one"),
+                                    Value::test_string("two"),
+                                    Value::test_string("three"),
+                                ],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(1), Value::test_int(2), Value::test_int(3)],
+                            ),
+                            Column::new(
+                                "a_in".to_string(),
+                                vec![
+                                    Value::test_bool(true),
+                                    Value::test_bool(true),
+                                    Value::test_bool(false),
+                                ],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Checks if elements from a series are contained in right series",
+                example: r#"let other = ([1 3 6] | polars into-df);
+            [5 6 6 6 8 8 8] | polars into-df | polars is-in $other"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "is_in".to_string(),
+                            vec![
+                                Value::test_bool(false),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["check", "contained", "is-contain", "match"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command_df(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => {
+                command_df(plugin, engine, call, lazy.collect(call.head)?)
+            }
+            PolarsPluginObject::NuExpression(expr) => command_expr(plugin, engine, call, expr),
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command_expr(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    expr: NuExpression,
+) -> Result<PipelineData, ShellError> {
+    let list: Vec<Value> = call.req(0)?;
+
+    let values = NuDataFrame::try_from_columns(vec![Column::new("list".to_string(), list)], None)?;
+    let list = values.as_series(call.head)?;
+
+    if matches!(list.dtype(), DataType::Object(..)) {
+        return Err(ShellError::IncompatibleParametersSingle {
+            msg: "Cannot use a mixed list as argument".into(),
+            span: call.head,
+        });
+    }
+
+    let expr: NuExpression = expr.to_polars().is_in(lit(list)).into();
+    to_pipeline_data(plugin, engine, call.head, expr)
+}
+
+fn command_df(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let other_value: Value = call.req(0)?;
+    let other_span = other_value.span();
+    let other_df = NuDataFrame::try_from_value(plugin, &other_value)?;
+    let other = other_df.as_series(other_span)?;
+    let series = df.as_series(call.head)?;
+
+    let mut res = is_in(&series, &other)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error finding in other".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+
+    res.rename("is_in");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ExprIsIn)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/lit.rs b/crates/nu_plugin_polars/src/dataframe/expressions/lit.rs
new file mode 100644
index 0000000000..48fc53b35d
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/lit.rs
@@ -0,0 +1,73 @@
+use crate::{
+    dataframe::values::NuExpression,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    record, Category, Example, LabeledError, PipelineData, Signature, SyntaxShape, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct ExprLit;
+
+impl PluginCommand for ExprLit {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars lit"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates a literal expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "literal",
+                SyntaxShape::Any,
+                "literal to construct the expression",
+            )
+            .input_output_type(Type::Any, Type::Custom("expression".into()))
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Created a literal expression and converts it to a nu object",
+            example: "polars lit 2 | polars into-nu",
+            result: Some(Value::test_record(record! {
+                "expr" =>  Value::test_string("literal"),
+                "value" => Value::test_string("2"),
+            })),
+        }]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["string", "literal", "expression"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        _input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let literal: Value = call.req(0)?;
+        let expr = NuExpression::try_from_value(plugin, &literal)?;
+        to_pipeline_data(plugin, engine, call.head, expr).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&ExprLit)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/mod.rs b/crates/nu_plugin_polars/src/dataframe/expressions/mod.rs
new file mode 100644
index 0000000000..055b836dac
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/mod.rs
@@ -0,0 +1,48 @@
+mod alias;
+mod arg_where;
+mod col;
+mod concat_str;
+mod datepart;
+mod expressions_macro;
+mod is_in;
+mod lit;
+mod otherwise;
+mod when;
+
+use nu_plugin::PluginCommand;
+
+pub use crate::dataframe::expressions::alias::ExprAlias;
+pub use crate::dataframe::expressions::arg_where::ExprArgWhere;
+pub use crate::dataframe::expressions::col::ExprCol;
+pub use crate::dataframe::expressions::concat_str::ExprConcatStr;
+pub use crate::dataframe::expressions::datepart::ExprDatePart;
+pub use crate::dataframe::expressions::expressions_macro::*;
+pub use crate::dataframe::expressions::is_in::ExprIsIn;
+pub use crate::dataframe::expressions::lit::ExprLit;
+pub use crate::dataframe::expressions::otherwise::ExprOtherwise;
+pub use crate::dataframe::expressions::when::ExprWhen;
+use crate::PolarsPlugin;
+
+pub(crate) fn expr_commands() -> Vec<Box<dyn PluginCommand<Plugin = PolarsPlugin>>> {
+    vec![
+        Box::new(ExprAlias),
+        Box::new(ExprArgWhere),
+        Box::new(ExprAggGroups),
+        Box::new(ExprCol),
+        Box::new(ExprConcatStr),
+        Box::new(ExprCount),
+        Box::new(ExprDatePart),
+        Box::new(ExprIsIn),
+        Box::new(ExprList),
+        Box::new(ExprLit),
+        Box::new(ExprNot),
+        Box::new(ExprMax),
+        Box::new(ExprMin),
+        Box::new(ExprOtherwise),
+        Box::new(ExprSum),
+        Box::new(ExprMean),
+        Box::new(ExprStd),
+        Box::new(ExprVar),
+        Box::new(ExprWhen),
+    ]
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/otherwise.rs b/crates/nu_plugin_polars/src/dataframe/expressions/otherwise.rs
new file mode 100644
index 0000000000..5a5764b205
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/otherwise.rs
@@ -0,0 +1,122 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression, NuWhen, NuWhenType},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct ExprOtherwise;
+
+impl PluginCommand for ExprOtherwise {
+    type Plugin = PolarsPlugin;
+    fn name(&self) -> &str {
+        "polars otherwise"
+    }
+
+    fn usage(&self) -> &str {
+        "Completes a when expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "otherwise expression",
+                SyntaxShape::Any,
+                "expression to apply when no when predicate matches",
+            )
+            .input_output_type(Type::Any, Type::Custom("expression".into()))
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create a when conditions",
+                example: "polars when ((polars col a) > 2) 4 | polars otherwise 5",
+                result: None,
+            },
+            Example {
+                description: "Create a when conditions",
+                example:
+                    "polars when ((polars col a) > 2) 4 | polars when ((polars col a) < 0) 6 | polars otherwise 0",
+                result: None,
+            },
+            Example {
+                description: "Create a new column for the dataframe",
+                example: r#"[[a b]; [6 2] [1 4] [4 1]]
+   | polars into-lazy
+   | polars with-column (
+    polars when ((polars col a) > 2) 4 | polars otherwise 5 | polars as c
+     )
+   | polars with-column (
+    polars when ((polars col a) > 5) 10 | polars when ((polars col a) < 2) 6 | polars otherwise 0 | polars as d
+     )
+   | polars collect"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(6), Value::test_int(1), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4), Value::test_int(1)],
+                            ),
+                            Column::new(
+                                "c".to_string(),
+                                vec![Value::test_int(4), Value::test_int(5), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "d".to_string(),
+                                vec![Value::test_int(10), Value::test_int(6), Value::test_int(0)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["condition", "else"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let otherwise_predicate: Value = call.req(0)?;
+        let otherwise_predicate = NuExpression::try_from_value(plugin, &otherwise_predicate)?;
+
+        let value = input.into_value(call.head);
+        let complete: NuExpression = match NuWhen::try_from_value(plugin, &value)?.when_type {
+            NuWhenType::Then(then) => then.otherwise(otherwise_predicate.to_polars()).into(),
+            NuWhenType::ChainedThen(chained_when) => chained_when
+                .otherwise(otherwise_predicate.to_polars())
+                .into(),
+        };
+        to_pipeline_data(plugin, engine, call.head, complete).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&ExprOtherwise)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/expressions/when.rs b/crates/nu_plugin_polars/src/dataframe/expressions/when.rs
new file mode 100644
index 0000000000..7d3b608e61
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/expressions/when.rs
@@ -0,0 +1,144 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression, NuWhen},
+    values::{to_pipeline_data, CustomValueSupport, NuWhenType},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
+};
+use polars::prelude::when;
+
+#[derive(Clone)]
+pub struct ExprWhen;
+
+impl PluginCommand for ExprWhen {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars when"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates and modifies a when expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "when expression",
+                SyntaxShape::Any,
+                "when expression used for matching",
+            )
+            .required(
+                "then expression",
+                SyntaxShape::Any,
+                "expression that will be applied when predicate is true",
+            )
+            .input_output_type(
+                Type::Custom("expression".into()),
+                Type::Custom("expression".into()),
+            )
+            .category(Category::Custom("expression".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create a when conditions",
+                example: "polars when ((polars col a) > 2) 4",
+                result: None,
+            },
+            Example {
+                description: "Create a when conditions",
+                example: "polars when ((polars col a) > 2) 4 | polars when ((polars col a) < 0) 6",
+                result: None,
+            },
+            Example {
+                description: "Create a new column for the dataframe",
+                example: r#"[[a b]; [6 2] [1 4] [4 1]]
+   | polars into-lazy
+   | polars with-column (
+    polars when ((polars col a) > 2) 4 | polars otherwise 5 | polars as c
+     )
+   | polars with-column (
+    polars when ((polars col a) > 5) 10 | polars when ((polars col a) < 2) 6 | polars otherwise 0 | polars as d
+     )
+   | polars collect"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(6), Value::test_int(1), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4), Value::test_int(1)],
+                            ),
+                            Column::new(
+                                "c".to_string(),
+                                vec![Value::test_int(4), Value::test_int(5), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "d".to_string(),
+                                vec![Value::test_int(10), Value::test_int(6), Value::test_int(0)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["condition", "match", "if", "else"]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let when_predicate: Value = call.req(0)?;
+        let when_predicate = NuExpression::try_from_value(plugin, &when_predicate)?;
+
+        let then_predicate: Value = call.req(1)?;
+        let then_predicate = NuExpression::try_from_value(plugin, &then_predicate)?;
+
+        let value = input.into_value(call.head);
+        let when_then: NuWhen = match value {
+            Value::Nothing { .. } => when(when_predicate.to_polars())
+                .then(then_predicate.to_polars())
+                .into(),
+            v => match NuWhen::try_from_value(plugin, &v)?.when_type {
+                NuWhenType::Then(when_then) => when_then
+                    .when(when_predicate.to_polars())
+                    .then(then_predicate.to_polars())
+                    .into(),
+                NuWhenType::ChainedThen(when_then_then) => when_then_then
+                    .when(when_predicate.to_polars())
+                    .then(then_predicate.to_polars())
+                    .into(),
+            },
+        };
+
+        to_pipeline_data(plugin, engine, call.head, when_then).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&ExprWhen)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/aggregate.rs b/crates/nu_plugin_polars/src/dataframe/lazy/aggregate.rs
new file mode 100644
index 0000000000..25ba033859
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/aggregate.rs
@@ -0,0 +1,210 @@
+use crate::{
+    dataframe::values::{NuExpression, NuLazyFrame, NuLazyGroupBy},
+    values::{to_pipeline_data, Column, CustomValueSupport, NuDataFrame},
+    PolarsPlugin,
+};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::{datatypes::DataType, prelude::Expr};
+
+#[derive(Clone)]
+pub struct LazyAggregate;
+
+impl PluginCommand for LazyAggregate {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars agg"
+    }
+
+    fn usage(&self) -> &str {
+        "Performs a series of aggregations from a group-by."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest(
+                "Group-by expressions",
+                SyntaxShape::Any,
+                "Expression(s) that define the aggregations to be applied",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Group by and perform an aggregation",
+                example: r#"[[a b]; [1 2] [1 4] [2 6] [2 4]]
+    | polars into-df
+    | polars group-by a
+    | polars agg [
+        (polars col b | polars min | polars as "b_min")
+        (polars col b | polars max | polars as "b_max")
+        (polars col b | polars sum | polars as "b_sum")
+     ]"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(2)],
+                            ),
+                            Column::new(
+                                "b_min".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "b_max".to_string(),
+                                vec![Value::test_int(4), Value::test_int(6)],
+                            ),
+                            Column::new(
+                                "b_sum".to_string(),
+                                vec![Value::test_int(6), Value::test_int(10)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Group by and perform an aggregation",
+                example: r#"[[a b]; [1 2] [1 4] [2 6] [2 4]]
+    | polars into-lazy
+    | polars group-by a
+    | polars agg [
+        (polars col b | polars min | polars as "b_min")
+        (polars col b | polars max | polars as "b_max")
+        (polars col b | polars sum | polars as "b_sum")
+     ]
+    | polars collect"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(2)],
+                            ),
+                            Column::new(
+                                "b_min".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "b_max".to_string(),
+                                vec![Value::test_int(4), Value::test_int(6)],
+                            ),
+                            Column::new(
+                                "b_sum".to_string(),
+                                vec![Value::test_int(6), Value::test_int(10)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let vals: Vec<Value> = call.rest(0)?;
+        let value = Value::list(vals, call.head);
+        let expressions = NuExpression::extract_exprs(plugin, value)?;
+
+        let group_by = NuLazyGroupBy::try_from_pipeline(plugin, input, call.head)?;
+
+        for expr in expressions.iter() {
+            if let Some(name) = get_col_name(expr) {
+                let dtype = group_by.schema.schema.get(name.as_str());
+
+                if matches!(dtype, Some(DataType::Object(..))) {
+                    return Err(ShellError::GenericError {
+                            error: "Object type column not supported for aggregation".into(),
+                            msg: format!("Column '{name}' is type Object"),
+                            span: Some(call.head),
+                            help: Some("Aggregations cannot be performed on Object type columns. Use dtype command to check column types".into()),
+                            inner: vec![],
+                        }).map_err(|e| e.into());
+                }
+            }
+        }
+
+        let polars = group_by.to_polars();
+        let lazy = NuLazyFrame::new(false, polars.agg(&expressions));
+        to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+    }
+}
+
+fn get_col_name(expr: &Expr) -> Option<String> {
+    match expr {
+        Expr::Column(column) => Some(column.to_string()),
+        Expr::Agg(agg) => match agg {
+            polars::prelude::AggExpr::Min { input: e, .. }
+            | polars::prelude::AggExpr::Max { input: e, .. }
+            | polars::prelude::AggExpr::Median(e)
+            | polars::prelude::AggExpr::NUnique(e)
+            | polars::prelude::AggExpr::First(e)
+            | polars::prelude::AggExpr::Last(e)
+            | polars::prelude::AggExpr::Mean(e)
+            | polars::prelude::AggExpr::Implode(e)
+            | polars::prelude::AggExpr::Count(e, _)
+            | polars::prelude::AggExpr::Sum(e)
+            | polars::prelude::AggExpr::AggGroups(e)
+            | polars::prelude::AggExpr::Std(e, _)
+            | polars::prelude::AggExpr::Var(e, _) => get_col_name(e.as_ref()),
+            polars::prelude::AggExpr::Quantile { expr, .. } => get_col_name(expr.as_ref()),
+        },
+        Expr::Filter { input: expr, .. }
+        | Expr::Slice { input: expr, .. }
+        | Expr::Cast { expr, .. }
+        | Expr::Sort { expr, .. }
+        | Expr::Gather { expr, .. }
+        | Expr::SortBy { expr, .. }
+        | Expr::Exclude(expr, _)
+        | Expr::Alias(expr, _)
+        | Expr::KeepName(expr)
+        | Expr::Explode(expr) => get_col_name(expr.as_ref()),
+        Expr::Ternary { .. }
+        | Expr::AnonymousFunction { .. }
+        | Expr::Function { .. }
+        | Expr::Columns(_)
+        | Expr::DtypeColumn(_)
+        | Expr::Literal(_)
+        | Expr::BinaryExpr { .. }
+        | Expr::Window { .. }
+        | Expr::Wildcard
+        | Expr::RenameAlias { .. }
+        | Expr::Len
+        | Expr::Nth(_)
+        | Expr::SubPlan(_, _)
+        | Expr::Selector(_) => None,
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyAggregate)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/collect.rs b/crates/nu_plugin_polars/src/dataframe/lazy/collect.rs
new file mode 100644
index 0000000000..9cfe903497
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/collect.rs
@@ -0,0 +1,98 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame},
+    values::{cant_convert_err, CustomValueSupport, PolarsPluginObject, PolarsPluginType},
+    Cacheable, PolarsPlugin,
+};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{Category, Example, LabeledError, PipelineData, Signature, Span, Type, Value};
+
+#[derive(Clone)]
+pub struct LazyCollect;
+
+impl PluginCommand for LazyCollect {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars collect"
+    }
+
+    fn usage(&self) -> &str {
+        "Collect lazy dataframe into eager dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "drop duplicates",
+            example: "[[a b]; [1 2] [3 4]] | polars into-lazy | polars collect",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_int(1), Value::test_int(3)],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(2), Value::test_int(4)],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuLazyFrame(lazy) => {
+                let eager = lazy.collect(call.head)?;
+                Ok(PipelineData::Value(
+                    eager.cache(plugin, engine)?.into_value(call.head),
+                    None,
+                ))
+            }
+            PolarsPluginObject::NuDataFrame(df) => {
+                // just return the dataframe, add to cache again to be safe
+                Ok(PipelineData::Value(
+                    df.cache(plugin, engine)?.into_value(call.head),
+                    None,
+                ))
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[PolarsPluginType::NuLazyFrame, PolarsPluginType::NuDataFrame],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&LazyCollect)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/explode.rs b/crates/nu_plugin_polars/src/dataframe/lazy/explode.rs
new file mode 100644
index 0000000000..e388630a8d
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/explode.rs
@@ -0,0 +1,175 @@
+use crate::dataframe::values::{Column, NuDataFrame, NuExpression, NuLazyFrame};
+use crate::values::{to_pipeline_data, CustomValueSupport, PolarsPluginObject};
+use crate::PolarsPlugin;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct LazyExplode;
+
+impl PluginCommand for LazyExplode {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars explode"
+    }
+
+    fn usage(&self) -> &str {
+        "Explodes a dataframe or creates a explode expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest(
+                "columns",
+                SyntaxShape::String,
+                "columns to explode, only applicable for dataframes",
+            )
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Explode the specified dataframe",
+                example: "[[id name hobbies]; [1 Mercy [Cycling Knitting]] [2 Bob [Skiing Football]]] | polars into-df | polars explode hobbies | polars collect",
+                result: Some(
+                    NuDataFrame::try_from_columns(vec![
+                        Column::new(
+                            "id".to_string(), 
+                            vec![
+                                Value::test_int(1),
+                                Value::test_int(1),
+                                Value::test_int(2),
+                                Value::test_int(2),
+                            ]),
+                        Column::new(
+                            "name".to_string(), 
+                            vec![
+                                Value::test_string("Mercy"),
+                                Value::test_string("Mercy"),
+                                Value::test_string("Bob"),
+                                Value::test_string("Bob"),
+                            ]),
+                        Column::new(
+                            "hobbies".to_string(), 
+                            vec![
+                                Value::test_string("Cycling"),
+                                Value::test_string("Knitting"),
+                                Value::test_string("Skiing"),
+                                Value::test_string("Football"),
+                            ]),
+                    ], None)
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                )
+            },
+            Example {
+                description: "Select a column and explode the values",
+                example: "[[id name hobbies]; [1 Mercy [Cycling Knitting]] [2 Bob [Skiing Football]]] | polars into-df | polars select (polars col hobbies | polars explode)",
+                result: Some(
+                    NuDataFrame::try_from_columns(vec![
+                        Column::new(
+                            "hobbies".to_string(), 
+                            vec![
+                                Value::test_string("Cycling"),
+                                Value::test_string("Knitting"),
+                                Value::test_string("Skiing"),
+                                Value::test_string("Football"),
+                            ]),
+                    ], None)
+                   .expect("simple df for test should not fail")
+                   .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        explode(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+pub(crate) fn explode(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let value = input.into_value(call.head);
+
+    match PolarsPluginObject::try_from_value(plugin, &value)? {
+        PolarsPluginObject::NuDataFrame(df) => {
+            let lazy = df.lazy();
+            explode_lazy(plugin, engine, call, lazy)
+        }
+        PolarsPluginObject::NuLazyFrame(lazy) => explode_lazy(plugin, engine, call, lazy),
+        PolarsPluginObject::NuExpression(expr) => explode_expr(plugin, engine, call, expr),
+        _ => Err(ShellError::CantConvert {
+            to_type: "dataframe or expression".into(),
+            from_type: value.get_type().to_string(),
+            span: call.head,
+            help: None,
+        }),
+    }
+}
+
+pub(crate) fn explode_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let columns = call
+        .positional
+        .iter()
+        .map(|e| e.as_str().map(|s| s.to_string()))
+        .collect::<Result<Vec<String>, ShellError>>()?;
+
+    let exploded = lazy
+        .to_polars()
+        .explode(columns.iter().map(AsRef::as_ref).collect::<Vec<&str>>());
+    let lazy = NuLazyFrame::from(exploded);
+
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+pub(crate) fn explode_expr(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    expr: NuExpression,
+) -> Result<PipelineData, ShellError> {
+    let expr: NuExpression = expr.to_polars().explode().into();
+    to_pipeline_data(plugin, engine, call.head, expr)
+}
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyExplode)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/fetch.rs b/crates/nu_plugin_polars/src/dataframe/lazy/fetch.rs
new file mode 100644
index 0000000000..77795778ce
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/fetch.rs
@@ -0,0 +1,100 @@
+use crate::dataframe::values::{Column, NuDataFrame};
+use crate::values::{to_pipeline_data, CustomValueSupport, NuLazyFrame};
+use crate::PolarsPlugin;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct LazyFetch;
+
+impl PluginCommand for LazyFetch {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars fetch"
+    }
+
+    fn usage(&self) -> &str {
+        "Collects the lazyframe to the selected rows."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "rows",
+                SyntaxShape::Int,
+                "number of rows to be fetched from lazyframe",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Fetch a rows from the dataframe",
+            example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars fetch 2",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_int(6), Value::test_int(4)],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(2), Value::test_int(2)],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let rows: i64 = call.req(0)?;
+        let value = input.into_value(call.head);
+        let lazy = NuLazyFrame::try_from_value_coerce(plugin, &value)?;
+
+        let mut eager: NuDataFrame = lazy
+            .to_polars()
+            .fetch(rows as usize)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error fetching rows".into(),
+                msg: e.to_string(),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?
+            .into();
+
+        // mark this as not from lazy so it doesn't get converted back to a lazy frame
+        eager.from_lazy = false;
+        to_pipeline_data(plugin, engine, call.head, eager).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyFetch)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/fill_nan.rs b/crates/nu_plugin_polars/src/dataframe/lazy/fill_nan.rs
new file mode 100644
index 0000000000..8329a7b410
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/fill_nan.rs
@@ -0,0 +1,189 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct LazyFillNA;
+
+impl PluginCommand for LazyFillNA {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars fill-nan"
+    }
+
+    fn usage(&self) -> &str {
+        "Replaces NaN values with the given expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "fill",
+                SyntaxShape::Any,
+                "Expression to use to fill the NAN values",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Fills the NaN values with 0",
+                example: "[1 2 NaN 3 NaN] | polars into-df | polars fill-nan 0",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0".to_string(),
+                            vec![
+                                Value::test_int(1),
+                                Value::test_int(2),
+                                Value::test_int(0),
+                                Value::test_int(3),
+                                Value::test_int(0),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("Df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Fills the NaN values of a whole dataframe",
+                example: "[[a b]; [0.2 1] [0.1 NaN]] | polars into-df | polars fill-nan 0",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_float(0.2), Value::test_float(0.1)],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_int(1), Value::test_int(0)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("Df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let fill: Value = call.req(0)?;
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => {
+                cmd_df(plugin, engine, call, df, fill, value.span())
+            }
+            PolarsPluginObject::NuLazyFrame(lazy) => cmd_df(
+                plugin,
+                engine,
+                call,
+                lazy.collect(value.span())?,
+                fill,
+                value.span(),
+            ),
+            PolarsPluginObject::NuExpression(expr) => {
+                Ok(cmd_expr(plugin, engine, call, expr, fill)?)
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn cmd_df(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    frame: NuDataFrame,
+    fill: Value,
+    val_span: Span,
+) -> Result<PipelineData, ShellError> {
+    let columns = frame.columns(val_span)?;
+    let dataframe = columns
+        .into_iter()
+        .map(|column| {
+            let column_name = column.name().to_string();
+            let values = column
+                .into_iter()
+                .map(|value| {
+                    let span = value.span();
+                    match value {
+                        Value::Float { val, .. } => {
+                            if val.is_nan() {
+                                fill.clone()
+                            } else {
+                                value
+                            }
+                        }
+                        Value::List { vals, .. } => {
+                            NuDataFrame::fill_list_nan(vals, span, fill.clone())
+                        }
+                        _ => value,
+                    }
+                })
+                .collect::<Vec<Value>>();
+            Column::new(column_name, values)
+        })
+        .collect::<Vec<Column>>();
+    let df = NuDataFrame::try_from_columns(dataframe, None)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+fn cmd_expr(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    expr: NuExpression,
+    fill: Value,
+) -> Result<PipelineData, ShellError> {
+    let fill = NuExpression::try_from_value(plugin, &fill)?.to_polars();
+    let expr: NuExpression = expr.to_polars().fill_nan(fill).into();
+
+    to_pipeline_data(plugin, engine, call.head, expr)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyFillNA)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/fill_null.rs b/crates/nu_plugin_polars/src/dataframe/lazy/fill_null.rs
new file mode 100644
index 0000000000..5c64dc620b
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/fill_null.rs
@@ -0,0 +1,127 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression, NuLazyFrame},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct LazyFillNull;
+
+impl PluginCommand for LazyFillNull {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars fill-null"
+    }
+
+    fn usage(&self) -> &str {
+        "Replaces NULL values with the given expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "fill",
+                SyntaxShape::Any,
+                "Expression to use to fill the null values",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Fills the null values by 0",
+            example: "[1 2 2 3 3] | polars into-df | polars shift 2 | polars fill-null 0",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_int(0),
+                            Value::test_int(0),
+                            Value::test_int(1),
+                            Value::test_int(2),
+                            Value::test_int(2),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let fill: Value = call.req(0)?;
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => cmd_lazy(plugin, engine, call, df.lazy(), fill),
+            PolarsPluginObject::NuLazyFrame(lazy) => cmd_lazy(plugin, engine, call, lazy, fill),
+            PolarsPluginObject::NuExpression(expr) => cmd_expr(plugin, engine, call, expr, fill),
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn cmd_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+    fill: Value,
+) -> Result<PipelineData, ShellError> {
+    let expr = NuExpression::try_from_value(plugin, &fill)?.to_polars();
+    let lazy = NuLazyFrame::new(lazy.from_eager, lazy.to_polars().fill_null(expr));
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+fn cmd_expr(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    expr: NuExpression,
+    fill: Value,
+) -> Result<PipelineData, ShellError> {
+    let fill = NuExpression::try_from_value(plugin, &fill)?.to_polars();
+    let expr: NuExpression = expr.to_polars().fill_null(fill).into();
+    to_pipeline_data(plugin, engine, call.head, expr)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyFillNull)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/filter.rs b/crates/nu_plugin_polars/src/dataframe/lazy/filter.rs
new file mode 100644
index 0000000000..481208d7f6
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/filter.rs
@@ -0,0 +1,104 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression, NuLazyFrame},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct LazyFilter;
+
+impl PluginCommand for LazyFilter {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars filter"
+    }
+
+    fn usage(&self) -> &str {
+        "Filter dataframe based in expression."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "filter expression",
+                SyntaxShape::Any,
+                "Expression that define the column selection",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Filter dataframe using an expression",
+            example:
+                "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars filter ((polars col a) >= 4)",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_int(6), Value::test_int(4)],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(2), Value::test_int(2)],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let expr_value: Value = call.req(0)?;
+        let filter_expr = NuExpression::try_from_value(plugin, &expr_value)?;
+        let pipeline_value = input.into_value(call.head);
+        let lazy = NuLazyFrame::try_from_value_coerce(plugin, &pipeline_value)?;
+        command(plugin, engine, call, lazy, filter_expr).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+    filter_expr: NuExpression,
+) -> Result<PipelineData, ShellError> {
+    let lazy = NuLazyFrame::new(
+        lazy.from_eager,
+        lazy.to_polars().filter(filter_expr.to_polars()),
+    );
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyFilter)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/flatten.rs b/crates/nu_plugin_polars/src/dataframe/lazy/flatten.rs
new file mode 100644
index 0000000000..93402bbe6a
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/flatten.rs
@@ -0,0 +1,125 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
+};
+
+use crate::{
+    dataframe::values::{Column, NuDataFrame},
+    values::CustomValueSupport,
+    PolarsPlugin,
+};
+
+use super::explode::explode;
+
+#[derive(Clone)]
+pub struct LazyFlatten;
+
+impl PluginCommand for LazyFlatten {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars flatten"
+    }
+
+    fn usage(&self) -> &str {
+        "An alias for polars explode."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest(
+                "columns",
+                SyntaxShape::String,
+                "columns to flatten, only applicable for dataframes",
+            )
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+Example {
+                description: "Flatten the specified dataframe",
+                example: "[[id name hobbies]; [1 Mercy [Cycling Knitting]] [2 Bob [Skiing Football]]] | polars into-df | polars flatten hobbies | polars collect",
+                result: Some(
+                    NuDataFrame::try_from_columns(vec![
+                        Column::new(
+                            "id".to_string(), 
+                            vec![
+                                Value::test_int(1),
+                                Value::test_int(1),
+                                Value::test_int(2),
+                                Value::test_int(2),
+                            ]),
+                        Column::new(
+                            "name".to_string(), 
+                            vec![
+                                Value::test_string("Mercy"),
+                                Value::test_string("Mercy"),
+                                Value::test_string("Bob"),
+                                Value::test_string("Bob"),
+                            ]),
+                        Column::new(
+                            "hobbies".to_string(), 
+                            vec![
+                                Value::test_string("Cycling"),
+                                Value::test_string("Knitting"),
+                                Value::test_string("Skiing"),
+                                Value::test_string("Football"),
+                            ]),
+                    ], None)
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                )
+            },
+        Example {
+                description: "Select a column and flatten the values",
+                example: "[[id name hobbies]; [1 Mercy [Cycling Knitting]] [2 Bob [Skiing Football]]] | polars into-df | polars select (polars col hobbies | polars flatten)",
+                result: Some(
+                    NuDataFrame::try_from_columns(vec![
+                        Column::new(
+                            "hobbies".to_string(), 
+                            vec![
+                                Value::test_string("Cycling"),
+                                Value::test_string("Knitting"),
+                                Value::test_string("Skiing"),
+                                Value::test_string("Football"),
+                            ]),
+                    ], None)
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        explode(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&LazyFlatten)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/groupby.rs b/crates/nu_plugin_polars/src/dataframe/lazy/groupby.rs
new file mode 100644
index 0000000000..765ffd003a
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/groupby.rs
@@ -0,0 +1,168 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression, NuLazyFrame, NuLazyGroupBy},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::Expr;
+
+#[derive(Clone)]
+pub struct ToLazyGroupBy;
+
+impl PluginCommand for ToLazyGroupBy {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars group-by"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates a group-by object that can be used for other aggregations."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest(
+                "Group-by expressions",
+                SyntaxShape::Any,
+                "Expression(s) that define the lazy group-by",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Group by and perform an aggregation",
+                example: r#"[[a b]; [1 2] [1 4] [2 6] [2 4]]
+    | polars into-df
+    | polars group-by a
+    | polars agg [
+        (polars col b | polars min | polars as "b_min")
+        (polars col b | polars max | polars as "b_max")
+        (polars col b | polars sum | polars as "b_sum")
+     ]"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(2)],
+                            ),
+                            Column::new(
+                                "b_min".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "b_max".to_string(),
+                                vec![Value::test_int(4), Value::test_int(6)],
+                            ),
+                            Column::new(
+                                "b_sum".to_string(),
+                                vec![Value::test_int(6), Value::test_int(10)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Group by and perform an aggregation",
+                example: r#"[[a b]; [1 2] [1 4] [2 6] [2 4]]
+    | polars into-lazy
+    | polars group-by a
+    | polars agg [
+        (polars col b | polars min | polars as "b_min")
+        (polars col b | polars max | polars as "b_max")
+        (polars col b | polars sum | polars as "b_sum")
+     ]
+    | polars collect"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_int(1), Value::test_int(2)],
+                            ),
+                            Column::new(
+                                "b_min".to_string(),
+                                vec![Value::test_int(2), Value::test_int(4)],
+                            ),
+                            Column::new(
+                                "b_max".to_string(),
+                                vec![Value::test_int(4), Value::test_int(6)],
+                            ),
+                            Column::new(
+                                "b_sum".to_string(),
+                                vec![Value::test_int(6), Value::test_int(10)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let vals: Vec<Value> = call.rest(0)?;
+        let expr_value = Value::list(vals, call.head);
+        let expressions = NuExpression::extract_exprs(plugin, expr_value)?;
+
+        if expressions
+            .iter()
+            .any(|expr| !matches!(expr, Expr::Column(..)))
+        {
+            let value: Value = call.req(0)?;
+            Err(ShellError::IncompatibleParametersSingle {
+                msg: "Expected only Col expressions".into(),
+                span: value.span(),
+            })?;
+        }
+
+        let pipeline_value = input.into_value(call.head);
+        let lazy = NuLazyFrame::try_from_value_coerce(plugin, &pipeline_value)?;
+        command(plugin, engine, call, lazy, expressions).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+    expressions: Vec<Expr>,
+) -> Result<PipelineData, ShellError> {
+    let group_by = lazy.to_polars().group_by(expressions);
+    let group_by = NuLazyGroupBy::new(group_by, lazy.from_eager, lazy.schema()?);
+    to_pipeline_data(plugin, engine, call.head, group_by)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ToLazyGroupBy)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/join.rs b/crates/nu_plugin_polars/src/dataframe/lazy/join.rs
new file mode 100644
index 0000000000..68784adc81
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/join.rs
@@ -0,0 +1,260 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression, NuLazyFrame},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{Expr, JoinType};
+
+#[derive(Clone)]
+pub struct LazyJoin;
+
+impl PluginCommand for LazyJoin {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars join"
+    }
+
+    fn usage(&self) -> &str {
+        "Joins a lazy frame with other lazy frame."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("other", SyntaxShape::Any, "LazyFrame to join with")
+            .required("left_on", SyntaxShape::Any, "Left column(s) to join on")
+            .required("right_on", SyntaxShape::Any, "Right column(s) to join on")
+            .switch(
+                "inner",
+                "inner joining between lazyframes (default)",
+                Some('i'),
+            )
+            .switch("left", "left join between lazyframes", Some('l'))
+            .switch("outer", "outer join between lazyframes", Some('o'))
+            .switch("cross", "cross join between lazyframes", Some('c'))
+            .named(
+                "suffix",
+                SyntaxShape::String,
+                "Suffix to use on columns with same name",
+                Some('s'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Join two lazy dataframes",
+                example: r#"let df_a = ([[a b c];[1 "a" 0] [2 "b" 1] [1 "c" 2] [1 "c" 3]] | polars into-lazy);
+    let df_b = ([["foo" "bar" "ham"];[1 "a" "let"] [2 "c" "var"] [3 "c" "const"]] | polars into-lazy);
+    $df_a | polars join $df_b a foo | polars collect"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![
+                                    Value::test_int(1),
+                                    Value::test_int(2),
+                                    Value::test_int(1),
+                                    Value::test_int(1),
+                                ],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![
+                                    Value::test_string("a"),
+                                    Value::test_string("b"),
+                                    Value::test_string("c"),
+                                    Value::test_string("c"),
+                                ],
+                            ),
+                            Column::new(
+                                "c".to_string(),
+                                vec![
+                                    Value::test_int(0),
+                                    Value::test_int(1),
+                                    Value::test_int(2),
+                                    Value::test_int(3),
+                                ],
+                            ),
+                            Column::new(
+                                "bar".to_string(),
+                                vec![
+                                    Value::test_string("a"),
+                                    Value::test_string("c"),
+                                    Value::test_string("a"),
+                                    Value::test_string("a"),
+                                ],
+                            ),
+                            Column::new(
+                                "ham".to_string(),
+                                vec![
+                                    Value::test_string("let"),
+                                    Value::test_string("var"),
+                                    Value::test_string("let"),
+                                    Value::test_string("let"),
+                                ],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Join one eager dataframe with a lazy dataframe",
+                example: r#"let df_a = ([[a b c];[1 "a" 0] [2 "b" 1] [1 "c" 2] [1 "c" 3]] | polars into-df);
+    let df_b = ([["foo" "bar" "ham"];[1 "a" "let"] [2 "c" "var"] [3 "c" "const"]] | polars into-lazy);
+    $df_a | polars join $df_b a foo"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![
+                                    Value::test_int(1),
+                                    Value::test_int(2),
+                                    Value::test_int(1),
+                                    Value::test_int(1),
+                                ],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![
+                                    Value::test_string("a"),
+                                    Value::test_string("b"),
+                                    Value::test_string("c"),
+                                    Value::test_string("c"),
+                                ],
+                            ),
+                            Column::new(
+                                "c".to_string(),
+                                vec![
+                                    Value::test_int(0),
+                                    Value::test_int(1),
+                                    Value::test_int(2),
+                                    Value::test_int(3),
+                                ],
+                            ),
+                            Column::new(
+                                "bar".to_string(),
+                                vec![
+                                    Value::test_string("a"),
+                                    Value::test_string("c"),
+                                    Value::test_string("a"),
+                                    Value::test_string("a"),
+                                ],
+                            ),
+                            Column::new(
+                                "ham".to_string(),
+                                vec![
+                                    Value::test_string("let"),
+                                    Value::test_string("var"),
+                                    Value::test_string("let"),
+                                    Value::test_string("let"),
+                                ],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let left = call.has_flag("left")?;
+        let outer = call.has_flag("outer")?;
+        let cross = call.has_flag("cross")?;
+
+        let how = if left {
+            JoinType::Left
+        } else if outer {
+            JoinType::Outer { coalesce: true }
+        } else if cross {
+            JoinType::Cross
+        } else {
+            JoinType::Inner
+        };
+
+        let other: Value = call.req(0)?;
+        let other = NuLazyFrame::try_from_value_coerce(plugin, &other)?;
+        let other = other.to_polars();
+
+        let left_on: Value = call.req(1)?;
+        let left_on = NuExpression::extract_exprs(plugin, left_on)?;
+
+        let right_on: Value = call.req(2)?;
+        let right_on = NuExpression::extract_exprs(plugin, right_on)?;
+
+        if left_on.len() != right_on.len() {
+            let right_on: Value = call.req(2)?;
+            Err(ShellError::IncompatibleParametersSingle {
+                msg: "The right column list has a different size to the left column list".into(),
+                span: right_on.span(),
+            })?;
+        }
+
+        // Checking that both list of expressions are made out of col expressions or strings
+        for (index, list) in &[(1usize, &left_on), (2, &left_on)] {
+            if list.iter().any(|expr| !matches!(expr, Expr::Column(..))) {
+                let value: Value = call.req(*index)?;
+                Err(ShellError::IncompatibleParametersSingle {
+                    msg: "Expected only a string, col expressions or list of strings".into(),
+                    span: value.span(),
+                })?;
+            }
+        }
+
+        let suffix: Option<String> = call.get_flag("suffix")?;
+        let suffix = suffix.unwrap_or_else(|| "_x".into());
+
+        let value = input.into_value(call.head);
+        let lazy = NuLazyFrame::try_from_value_coerce(plugin, &value)?;
+        let from_eager = lazy.from_eager;
+        let lazy = lazy.to_polars();
+
+        let lazy = lazy
+            .join_builder()
+            .with(other)
+            .left_on(left_on)
+            .right_on(right_on)
+            .how(how)
+            .force_parallel(true)
+            .suffix(suffix)
+            .finish();
+
+        let lazy = NuLazyFrame::new(from_eager, lazy);
+        to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyJoin)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/macro_commands.rs b/crates/nu_plugin_polars/src/dataframe/lazy/macro_commands.rs
new file mode 100644
index 0000000000..38968c2bda
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/macro_commands.rs
@@ -0,0 +1,225 @@
+/// Definition of multiple lazyframe commands using a macro rule
+/// All of these commands have an identical body and only require
+/// to have a change in the name, description and function
+use crate::dataframe::values::{Column, NuDataFrame, NuLazyFrame};
+use crate::values::{to_pipeline_data, CustomValueSupport};
+use crate::PolarsPlugin;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{Category, Example, LabeledError, PipelineData, Signature, Span, Type, Value};
+
+macro_rules! lazy_command {
+    ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident, $test: ident) => {
+        #[derive(Clone)]
+        pub struct $command;
+
+        impl PluginCommand for $command {
+            type Plugin = PolarsPlugin;
+
+            fn name(&self) -> &str {
+                $name
+            }
+
+            fn usage(&self) -> &str {
+                $desc
+            }
+
+            fn signature(&self) -> Signature {
+                Signature::build(self.name())
+                    .usage($desc)
+                    .input_output_type(
+                        Type::Custom("dataframe".into()),
+                        Type::Custom("dataframe".into()),
+                    )
+                    .category(Category::Custom("lazyframe".into()))
+            }
+
+            fn examples(&self) -> Vec<Example> {
+                $examples
+            }
+
+            fn run(
+                &self,
+                plugin: &Self::Plugin,
+                engine: &EngineInterface,
+                call: &EvaluatedCall,
+                input: PipelineData,
+            ) -> Result<PipelineData, LabeledError> {
+                let lazy = NuLazyFrame::try_from_pipeline_coerce(plugin, input, call.head)
+                    .map_err(LabeledError::from)?;
+                let lazy = NuLazyFrame::new(lazy.from_eager, lazy.to_polars().$func());
+                to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+            }
+        }
+
+        #[cfg(test)]
+        mod $test {
+            use super::*;
+            use crate::test::test_polars_plugin_command;
+            use nu_protocol::ShellError;
+
+            #[test]
+            fn test_examples() -> Result<(), ShellError> {
+                test_polars_plugin_command(&$command)
+            }
+        }
+    };
+
+    ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident, $test: ident, $ddot: expr) => {
+        #[derive(Clone)]
+        pub struct $command;
+
+        impl PluginCommand for $command {
+            type Plugin = PolarsPlugin;
+
+            fn signature(&self) -> Signature {
+                Signature::build($name)
+                    .usage($desc)
+                    .input_output_type(
+                        Type::Custom("dataframe".into()),
+                        Type::Custom("dataframe".into()),
+                    )
+                    .category(Category::Custom("lazyframe".into()))
+                    .plugin_examples($examples)
+            }
+
+            fn run(
+                &self,
+                _plugin: &Self::Plugin,
+                engine: &EngineInterface,
+                call: &EvaluatedCall,
+                input: PipelineData,
+            ) -> Result<PipelineData, LabeledError> {
+                let lazy = NuLazyFrame::try_from_pipeline_coerce(plugin, input, call.head)
+                    .map_err(LabeledError::from)?;
+                let lazy = NuLazyFrame::new(lazy.from_eager, lazy.into_polars().$func($ddot));
+                to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+            }
+        }
+
+        #[cfg(test)]
+        mod $test {
+            use super::*;
+            use crate::test::test_polars_plugin_command;
+            use nu_protocol::ShellError;
+
+            #[test]
+            fn test_examples() -> Result<(), ShellError> {
+                test_polars_plugin_command(&$command)
+            }
+        }
+    };
+
+    ($command: ident, $name: expr, $desc: expr, $examples: expr, $func: ident?, $test: ident) => {
+        #[derive(Clone)]
+        pub struct $command;
+
+        impl PluginCommand for $command {
+            type Plugin = PolarsPlugin;
+
+            fn name(&self) -> &str {
+                $name
+            }
+
+            fn usage(&self) -> &str {
+                $desc
+            }
+            fn signature(&self) -> Signature {
+                Signature::build(self.name())
+                    .input_output_type(
+                        Type::Custom("dataframe".into()),
+                        Type::Custom("dataframe".into()),
+                    )
+                    .category(Category::Custom("lazyframe".into()))
+            }
+
+            fn examples(&self) -> Vec<Example> {
+                $examples
+            }
+
+            fn run(
+                &self,
+                plugin: &Self::Plugin,
+                engine: &EngineInterface,
+                call: &EvaluatedCall,
+                input: PipelineData,
+            ) -> Result<PipelineData, LabeledError> {
+                let lazy = NuLazyFrame::try_from_pipeline_coerce(plugin, input, call.head)
+                    .map_err(LabeledError::from)?;
+
+                let lazy = NuLazyFrame::new(
+                    lazy.from_eager,
+                    lazy.to_polars()
+                        .$func()
+                        .map_err(|e| ShellError::GenericError {
+                            error: "Dataframe Error".into(),
+                            msg: e.to_string(),
+                            help: None,
+                            span: None,
+                            inner: vec![],
+                        })
+                        .map_err(LabeledError::from)?,
+                );
+
+                to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+            }
+        }
+
+        #[cfg(test)]
+        mod $test {
+            use super::*;
+            use crate::test::test_polars_plugin_command;
+            use nu_protocol::ShellError;
+
+            #[test]
+            fn test_examples() -> Result<(), ShellError> {
+                test_polars_plugin_command(&$command)
+            }
+        }
+    };
+}
+
+// LazyReverse command
+// Expands to a command definition for reverse
+lazy_command!(
+    LazyReverse,
+    "polars reverse",
+    "Reverses the LazyFrame",
+    vec![Example {
+        description: "Reverses the dataframe.",
+        example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars reverse",
+        result: Some(
+            NuDataFrame::try_from_columns(
+                vec![
+                    Column::new(
+                        "a".to_string(),
+                        vec![Value::test_int(2), Value::test_int(4), Value::test_int(6),],
+                    ),
+                    Column::new(
+                        "b".to_string(),
+                        vec![Value::test_int(2), Value::test_int(2), Value::test_int(2),],
+                    ),
+                ],
+                None
+            )
+            .expect("simple df for test should not fail")
+            .into_value(Span::test_data()),
+        ),
+    },],
+    reverse,
+    test_reverse
+);
+
+// LazyCache command
+// Expands to a command definition for cache
+lazy_command!(
+    LazyCache,
+    "polars cache",
+    "Caches operations in a new LazyFrame.",
+    vec![Example {
+        description: "Caches the result into a new LazyFrame",
+        example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars reverse | polars cache",
+        result: None,
+    }],
+    cache,
+    test_cache
+);
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/median.rs b/crates/nu_plugin_polars/src/dataframe/lazy/median.rs
new file mode 100644
index 0000000000..da21a1d7eb
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/median.rs
@@ -0,0 +1,143 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuLazyFrame},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, NuExpression, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+#[derive(Clone)]
+pub struct LazyMedian;
+
+impl PluginCommand for LazyMedian {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars median"
+    }
+
+    fn usage(&self) -> &str {
+        "Median value from columns in a dataframe or creates expression for an aggregation"
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Median aggregation for a group-by",
+                example: r#"[[a b]; [one 2] [one 4] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars median)"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_string("one"), Value::test_string("two")],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_float(3.0), Value::test_float(1.0)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Median value from columns in a dataframe",
+                example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars median",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new("a".to_string(), vec![Value::test_float(4.0)]),
+                            Column::new("b".to_string(), vec![Value::test_float(2.0)]),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command(plugin, engine, call, df.lazy()),
+            PolarsPluginObject::NuLazyFrame(lazy) => command(plugin, engine, call, lazy),
+            PolarsPluginObject::NuExpression(expr) => {
+                let expr: NuExpression = expr.to_polars().median().into();
+                to_pipeline_data(plugin, engine, call.head, expr)
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let polars_lazy = lazy
+        .to_polars()
+        .median()
+        .map_err(|e| ShellError::GenericError {
+            error: format!("Error in median operation: {e}"),
+            msg: "".into(),
+            help: None,
+            span: None,
+            inner: vec![],
+        })?;
+    let lazy = NuLazyFrame::new(lazy.from_eager, polars_lazy);
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyMedian)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/mod.rs b/crates/nu_plugin_polars/src/dataframe/lazy/mod.rs
new file mode 100644
index 0000000000..e70143e6ce
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/mod.rs
@@ -0,0 +1,57 @@
+mod aggregate;
+mod collect;
+mod explode;
+mod fetch;
+mod fill_nan;
+mod fill_null;
+mod filter;
+mod flatten;
+pub mod groupby;
+mod join;
+mod macro_commands;
+mod median;
+mod quantile;
+mod select;
+mod sort_by_expr;
+mod to_lazy;
+
+use nu_plugin::PluginCommand;
+
+pub use crate::dataframe::lazy::aggregate::LazyAggregate;
+pub use crate::dataframe::lazy::collect::LazyCollect;
+use crate::dataframe::lazy::fetch::LazyFetch;
+use crate::dataframe::lazy::fill_nan::LazyFillNA;
+pub use crate::dataframe::lazy::fill_null::LazyFillNull;
+use crate::dataframe::lazy::filter::LazyFilter;
+use crate::dataframe::lazy::groupby::ToLazyGroupBy;
+use crate::dataframe::lazy::join::LazyJoin;
+pub(crate) use crate::dataframe::lazy::macro_commands::*;
+use crate::dataframe::lazy::quantile::LazyQuantile;
+pub(crate) use crate::dataframe::lazy::select::LazySelect;
+use crate::dataframe::lazy::sort_by_expr::LazySortBy;
+pub use crate::dataframe::lazy::to_lazy::ToLazyFrame;
+use crate::PolarsPlugin;
+pub use explode::LazyExplode;
+pub use flatten::LazyFlatten;
+
+pub(crate) fn lazy_commands() -> Vec<Box<dyn PluginCommand<Plugin = PolarsPlugin>>> {
+    vec![
+        Box::new(LazyAggregate),
+        Box::new(LazyCache),
+        Box::new(LazyCollect),
+        Box::new(LazyExplode),
+        Box::new(LazyFetch),
+        Box::new(LazyFillNA),
+        Box::new(LazyFillNull),
+        Box::new(LazyFilter),
+        Box::new(LazyFlatten),
+        Box::new(LazyJoin),
+        Box::new(median::LazyMedian),
+        Box::new(LazyReverse),
+        Box::new(LazySelect),
+        Box::new(LazySortBy),
+        Box::new(LazyQuantile),
+        Box::new(ToLazyFrame),
+        Box::new(ToLazyGroupBy),
+    ]
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/quantile.rs b/crates/nu_plugin_polars/src/dataframe/lazy/quantile.rs
new file mode 100644
index 0000000000..7dc6bb5c18
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/quantile.rs
@@ -0,0 +1,160 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuLazyFrame},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, NuExpression, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{lit, QuantileInterpolOptions};
+
+#[derive(Clone)]
+pub struct LazyQuantile;
+
+impl PluginCommand for LazyQuantile {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars quantile"
+    }
+
+    fn usage(&self) -> &str {
+        "Aggregates the columns to the selected quantile."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "quantile",
+                SyntaxShape::Number,
+                "quantile value for quantile operation",
+            )
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "quantile value from columns in a dataframe",
+                example: "[[a b]; [6 2] [1 4] [4 1]] | polars into-df | polars quantile 0.5",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new("a".to_string(), vec![Value::test_float(4.0)]),
+                            Column::new("b".to_string(), vec![Value::test_float(2.0)]),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Quantile aggregation for a group-by",
+                example: r#"[[a b]; [one 2] [one 4] [two 1]]
+    | polars into-df
+    | polars group-by a
+    | polars agg (polars col b | polars quantile 0.5)"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![
+                            Column::new(
+                                "a".to_string(),
+                                vec![Value::test_string("one"), Value::test_string("two")],
+                            ),
+                            Column::new(
+                                "b".to_string(),
+                                vec![Value::test_float(4.0), Value::test_float(1.0)],
+                            ),
+                        ],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+        let quantile: f64 = call.req(0)?;
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => {
+                command(plugin, engine, call, df.lazy(), quantile)
+            }
+            PolarsPluginObject::NuLazyFrame(lazy) => command(plugin, engine, call, lazy, quantile),
+            PolarsPluginObject::NuExpression(expr) => {
+                let expr: NuExpression = expr
+                    .to_polars()
+                    .quantile(lit(quantile), QuantileInterpolOptions::default())
+                    .into();
+                to_pipeline_data(plugin, engine, call.head, expr)
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+    quantile: f64,
+) -> Result<PipelineData, ShellError> {
+    let lazy = NuLazyFrame::new(
+        lazy.from_eager,
+        lazy.to_polars()
+            .quantile(lit(quantile), QuantileInterpolOptions::default())
+            .map_err(|e| ShellError::GenericError {
+                error: "Dataframe Error".into(),
+                msg: e.to_string(),
+                help: None,
+                span: None,
+                inner: vec![],
+            })?,
+    );
+
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazyQuantile)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/select.rs b/crates/nu_plugin_polars/src/dataframe/lazy/select.rs
new file mode 100644
index 0000000000..4da89cf218
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/select.rs
@@ -0,0 +1,85 @@
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression, NuLazyFrame},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
+};
+#[derive(Clone)]
+pub struct LazySelect;
+
+impl PluginCommand for LazySelect {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars select"
+    }
+
+    fn usage(&self) -> &str {
+        "Selects columns from lazyframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest(
+                "select expressions",
+                SyntaxShape::Any,
+                "Expression(s) that define the column selection",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Select a column from the dataframe",
+            example: "[[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars select a",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "a".to_string(),
+                        vec![Value::test_int(6), Value::test_int(4), Value::test_int(2)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let vals: Vec<Value> = call.rest(0)?;
+        let expr_value = Value::list(vals, call.head);
+        let expressions = NuExpression::extract_exprs(plugin, expr_value)?;
+
+        let pipeline_value = input.into_value(call.head);
+        let lazy = NuLazyFrame::try_from_value_coerce(plugin, &pipeline_value)?;
+        let lazy = NuLazyFrame::new(lazy.from_eager, lazy.to_polars().select(&expressions));
+        to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use crate::test::test_polars_plugin_command;
+
+    use super::*;
+
+    #[test]
+    fn test_examples() -> Result<(), nu_protocol::ShellError> {
+        test_polars_plugin_command(&LazySelect)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/sort_by_expr.rs b/crates/nu_plugin_polars/src/dataframe/lazy/sort_by_expr.rs
new file mode 100644
index 0000000000..5e4f3a5e88
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/sort_by_expr.rs
@@ -0,0 +1,160 @@
+use super::super::values::NuLazyFrame;
+use crate::{
+    dataframe::values::{Column, NuDataFrame, NuExpression},
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+#[derive(Clone)]
+pub struct LazySortBy;
+
+impl PluginCommand for LazySortBy {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars sort-by"
+    }
+
+    fn usage(&self) -> &str {
+        "Sorts a lazy dataframe based on expression(s)."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .rest(
+                "sort expression",
+                SyntaxShape::Any,
+                "sort expression for the dataframe",
+            )
+            .named(
+                "reverse",
+                SyntaxShape::List(Box::new(SyntaxShape::Boolean)),
+                "Reverse sorting. Default is false",
+                Some('r'),
+            )
+            .switch(
+                "nulls-last",
+                "nulls are shown last in the dataframe",
+                Some('n'),
+            )
+            .switch("maintain-order", "Maintains order during sort", Some('m'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Sort dataframe by one column",
+                example: "[[a b]; [6 2] [1 4] [4 1]] | polars into-df | polars sort-by a",
+                result: Some(
+                    NuDataFrame::try_from_columns(vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![Value::test_int(1), Value::test_int(4), Value::test_int(6)],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![Value::test_int(4), Value::test_int(1), Value::test_int(2)],
+                        ),
+                    ], None)
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Sort column using two columns",
+                example:
+                    "[[a b]; [6 2] [1 1] [1 4] [2 4]] | polars into-df | polars sort-by [a b] -r [false true]",
+                result: Some(
+                    NuDataFrame::try_from_columns(vec![
+                        Column::new(
+                            "a".to_string(),
+                            vec![
+                                Value::test_int(1),
+                                Value::test_int(1),
+                                Value::test_int(2),
+                                Value::test_int(6),
+                            ],
+                        ),
+                        Column::new(
+                            "b".to_string(),
+                            vec![
+                                Value::test_int(4),
+                                Value::test_int(1),
+                                Value::test_int(4),
+                                Value::test_int(2),
+                            ],
+                        ),
+                    ], None)
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let vals: Vec<Value> = call.rest(0)?;
+        let expr_value = Value::list(vals, call.head);
+        let expressions = NuExpression::extract_exprs(plugin, expr_value)?;
+        let nulls_last = call.has_flag("nulls-last")?;
+        let maintain_order = call.has_flag("maintain-order")?;
+
+        let reverse: Option<Vec<bool>> = call.get_flag("reverse")?;
+        let reverse = match reverse {
+            Some(list) => {
+                if expressions.len() != list.len() {
+                    let span = call
+                        .get_flag::<Value>("reverse")?
+                        .expect("already checked and it exists")
+                        .span();
+                    Err(ShellError::GenericError {
+                        error: "Incorrect list size".into(),
+                        msg: "Size doesn't match expression list".into(),
+                        span: Some(span),
+                        help: None,
+                        inner: vec![],
+                    })?
+                } else {
+                    list
+                }
+            }
+            None => expressions.iter().map(|_| false).collect::<Vec<bool>>(),
+        };
+
+        let pipeline_value = input.into_value(call.head);
+        let lazy = NuLazyFrame::try_from_value_coerce(plugin, &pipeline_value)?;
+        let lazy = NuLazyFrame::new(
+            lazy.from_eager,
+            lazy.to_polars()
+                .sort_by_exprs(&expressions, reverse, nulls_last, maintain_order),
+        );
+        to_pipeline_data(plugin, engine, call.head, lazy).map_err(LabeledError::from)
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&LazySortBy)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/lazy/to_lazy.rs b/crates/nu_plugin_polars/src/dataframe/lazy/to_lazy.rs
new file mode 100644
index 0000000000..2991a0fb33
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/lazy/to_lazy.rs
@@ -0,0 +1,61 @@
+use crate::{dataframe::values::NuSchema, values::CustomValueSupport, Cacheable, PolarsPlugin};
+
+use super::super::values::{NuDataFrame, NuLazyFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{Category, Example, LabeledError, PipelineData, Signature, SyntaxShape, Type};
+
+#[derive(Clone)]
+pub struct ToLazyFrame;
+
+impl PluginCommand for ToLazyFrame {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars into-lazy"
+    }
+
+    fn usage(&self) -> &str {
+        "Converts a dataframe into a lazy dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .named(
+                "schema",
+                SyntaxShape::Record(vec![]),
+                r#"Polars Schema in format [{name: str}]. CSV, JSON, and JSONL files"#,
+                Some('s'),
+            )
+            .input_output_type(Type::Any, Type::Custom("dataframe".into()))
+            .category(Category::Custom("lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Takes a dictionary and creates a lazy dataframe",
+            example: "[[a b];[1 2] [3 4]] | polars into-lazy",
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let maybe_schema = call
+            .get_flag("schema")?
+            .map(|schema| NuSchema::try_from(&schema))
+            .transpose()?;
+
+        let df = NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema)?;
+        let lazy = NuLazyFrame::from_dataframe(df);
+        Ok(PipelineData::Value(
+            lazy.cache(plugin, engine)?.into_value(call.head),
+            None,
+        ))
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/mod.rs b/crates/nu_plugin_polars/src/dataframe/mod.rs
new file mode 100644
index 0000000000..e41ef5bc1a
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/mod.rs
@@ -0,0 +1,19 @@
+use nu_protocol::{ShellError, Span};
+
+pub mod eager;
+pub mod expressions;
+pub mod lazy;
+pub mod series;
+pub mod stub;
+mod utils;
+pub mod values;
+
+pub fn missing_flag_error(flag: &str, span: Span) -> ShellError {
+    ShellError::GenericError {
+        error: format!("Missing flag: {flag}"),
+        msg: "".into(),
+        span: Some(span),
+        help: None,
+        inner: vec![],
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/all_false.rs b/crates/nu_plugin_polars/src/dataframe/series/all_false.rs
new file mode 100644
index 0000000000..171aa20333
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/all_false.rs
@@ -0,0 +1,119 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct AllFalse;
+
+impl PluginCommand for AllFalse {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars all-false"
+    }
+
+    fn usage(&self) -> &str {
+        "Returns true if all values are false."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Returns true if all values are false",
+                example: "[false false false] | polars into-df | polars all-false",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "all_false".to_string(),
+                            vec![Value::test_bool(true)],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Checks the result from a comparison",
+                example: r#"let s = ([5 6 2 10] | polars into-df);
+    let res = ($s > 9);
+    $res | polars all-false"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "all_false".to_string(),
+                            vec![Value::test_bool(false)],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let series = df.as_series(call.head)?;
+    let bool = series.bool().map_err(|_| ShellError::GenericError {
+        error: "Error converting to bool".into(),
+        msg: "all-false only works with series of type bool".into(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let value = Value::bool(!bool.any(), call.head);
+
+    let df = NuDataFrame::try_from_columns(
+        vec![Column::new("all_false".to_string(), vec![value])],
+        None,
+    )?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&AllFalse)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/all_true.rs b/crates/nu_plugin_polars/src/dataframe/series/all_true.rs
new file mode 100644
index 0000000000..de69b29d72
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/all_true.rs
@@ -0,0 +1,119 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct AllTrue;
+
+impl PluginCommand for AllTrue {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars all-true"
+    }
+
+    fn usage(&self) -> &str {
+        "Returns true if all values are true."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Returns true if all values are true",
+                example: "[true true true] | polars into-df | polars all-true",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "all_true".to_string(),
+                            vec![Value::test_bool(true)],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Checks the result from a comparison",
+                example: r#"let s = ([5 6 2 8] | polars into-df);
+    let res = ($s > 9);
+    $res | polars all-true"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "all_true".to_string(),
+                            vec![Value::test_bool(false)],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let series = df.as_series(call.head)?;
+    let bool = series.bool().map_err(|_| ShellError::GenericError {
+        error: "Error converting to bool".into(),
+        msg: "all-false only works with series of type bool".into(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let value = Value::bool(bool.all(), call.head);
+
+    let df = NuDataFrame::try_from_columns(
+        vec![Column::new("all_true".to_string(), vec![value])],
+        None,
+    )?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&AllTrue)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/arg_max.rs b/crates/nu_plugin_polars/src/dataframe/series/arg_max.rs
new file mode 100644
index 0000000000..e62999066e
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/arg_max.rs
@@ -0,0 +1,96 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::{ArgAgg, IntoSeries, NewChunkedArray, UInt32Chunked};
+
+#[derive(Clone)]
+pub struct ArgMax;
+
+impl PluginCommand for ArgMax {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars arg-max"
+    }
+
+    fn usage(&self) -> &str {
+        "Return index for max value in series."
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["argmax", "maximum", "most", "largest", "greatest"]
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns index for max value",
+            example: "[1 3 2] | polars into-df | polars arg-max",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new("arg_max".to_string(), vec![Value::test_int(1)])],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let res = series.arg_max();
+    let chunked = match res {
+        Some(index) => UInt32Chunked::from_slice("arg_max", &[index as u32]),
+        None => UInt32Chunked::from_slice("arg_max", &[]),
+    };
+
+    let res = chunked.into_series();
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ArgMax)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/arg_min.rs b/crates/nu_plugin_polars/src/dataframe/series/arg_min.rs
new file mode 100644
index 0000000000..80876e2736
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/arg_min.rs
@@ -0,0 +1,96 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::{ArgAgg, IntoSeries, NewChunkedArray, UInt32Chunked};
+
+#[derive(Clone)]
+pub struct ArgMin;
+
+impl PluginCommand for ArgMin {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars arg-min"
+    }
+
+    fn usage(&self) -> &str {
+        "Return index for min value in series."
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["argmin", "minimum", "least", "smallest", "lowest"]
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns index for min value",
+            example: "[1 3 2] | polars into-df | polars arg-min",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new("arg_min".to_string(), vec![Value::test_int(0)])],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let res = series.arg_min();
+    let chunked = match res {
+        Some(index) => UInt32Chunked::from_slice("arg_min", &[index as u32]),
+        None => UInt32Chunked::from_slice("arg_min", &[]),
+    };
+
+    let res = chunked.into_series();
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ArgMin)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/cumulative.rs b/crates/nu_plugin_polars/src/dataframe/series/cumulative.rs
new file mode 100644
index 0000000000..420a98c9c5
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/cumulative.rs
@@ -0,0 +1,159 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Spanned,
+    SyntaxShape, Type, Value,
+};
+use polars::prelude::{DataType, IntoSeries};
+use polars_ops::prelude::{cum_max, cum_min, cum_sum};
+
+enum CumulativeType {
+    Min,
+    Max,
+    Sum,
+}
+
+impl CumulativeType {
+    fn from_str(roll_type: &str, span: Span) -> Result<Self, ShellError> {
+        match roll_type {
+            "min" => Ok(Self::Min),
+            "max" => Ok(Self::Max),
+            "sum" => Ok(Self::Sum),
+            _ => Err(ShellError::GenericError {
+                error: "Wrong operation".into(),
+                msg: "Operation not valid for cumulative".into(),
+                span: Some(span),
+                help: Some("Allowed values: max, min, sum".into()),
+                inner: vec![],
+            }),
+        }
+    }
+
+    fn to_str(&self) -> &'static str {
+        match self {
+            CumulativeType::Min => "cumulative_min",
+            CumulativeType::Max => "cumulative_max",
+            CumulativeType::Sum => "cumulative_sum",
+        }
+    }
+}
+
+#[derive(Clone)]
+pub struct Cumulative;
+
+impl PluginCommand for Cumulative {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars cumulative"
+    }
+
+    fn usage(&self) -> &str {
+        "Cumulative calculation for a series."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("type", SyntaxShape::String, "rolling operation")
+            .switch("reverse", "Reverse cumulative calculation", Some('r'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Cumulative sum for a series",
+            example: "[1 2 3 4 5] | polars into-df | polars cumulative sum",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0_cumulative_sum".to_string(),
+                        vec![
+                            Value::test_int(1),
+                            Value::test_int(3),
+                            Value::test_int(6),
+                            Value::test_int(10),
+                            Value::test_int(15),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let cum_type: Spanned<String> = call.req(0)?;
+    let reverse = call.has_flag("reverse")?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    if let DataType::Object(..) = series.dtype() {
+        return Err(ShellError::GenericError {
+            error: "Found object series".into(),
+            msg: "Series of type object cannot be used for cumulative operation".into(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        });
+    }
+
+    let cum_type = CumulativeType::from_str(&cum_type.item, cum_type.span)?;
+    let mut res = match cum_type {
+        CumulativeType::Max => cum_max(&series, reverse),
+        CumulativeType::Min => cum_min(&series, reverse),
+        CumulativeType::Sum => cum_sum(&series, reverse),
+    }
+    .map_err(|e| ShellError::GenericError {
+        error: "Error creating cumulative".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let name = format!("{}_{}", series.name(), cum_type.to_str());
+    res.rename(&name);
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Cumulative)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/as_date.rs b/crates/nu_plugin_polars/src/dataframe/series/date/as_date.rs
new file mode 100644
index 0000000000..8d613917b0
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/as_date.rs
@@ -0,0 +1,101 @@
+use crate::{values::to_pipeline_data, PolarsPlugin};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, SyntaxShape, Type,
+};
+use polars::prelude::{IntoSeries, StringMethods};
+
+#[derive(Clone)]
+pub struct AsDate;
+
+impl PluginCommand for AsDate {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars as-date"
+    }
+
+    fn usage(&self) -> &str {
+        r#"Converts string to date."#
+    }
+
+    fn extra_usage(&self) -> &str {
+        r#"Format example:
+        "%Y-%m-%d"    => 2021-12-31
+        "%d-%m-%Y"    => 31-12-2021
+        "%Y%m%d"      => 2021319 (2021-03-19)"#
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("format", SyntaxShape::String, "formatting date string")
+            .switch("not-exact", "the format string may be contained in the date (e.g. foo-2021-01-01-bar could match 2021-01-01)", Some('n'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Converts string to date",
+            example: r#"["2021-12-30" "2021-12-31"] | polars into-df | polars as-date "%Y-%m-%d""#,
+            result: None,
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let format: String = call.req(0)?;
+    let not_exact = call.has_flag("not-exact")?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+    let casted = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error casting to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = if not_exact {
+        casted.as_date_not_exact(Some(format.as_str()))
+    } else {
+        casted.as_date(Some(format.as_str()), false)
+    };
+
+    let mut res = res
+        .map_err(|e| ShellError::GenericError {
+            error: "Error creating datetime".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+
+    res.rename("date");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/as_datetime.rs b/crates/nu_plugin_polars/src/dataframe/series/date/as_datetime.rs
new file mode 100644
index 0000000000..1f8d151819
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/as_datetime.rs
@@ -0,0 +1,198 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use chrono::DateTime;
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{IntoSeries, StringMethods, TimeUnit};
+
+#[derive(Clone)]
+pub struct AsDateTime;
+
+impl PluginCommand for AsDateTime {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars as-datetime"
+    }
+
+    fn usage(&self) -> &str {
+        r#"Converts string to datetime."#
+    }
+
+    fn extra_usage(&self) -> &str {
+        r#"Format example:
+        "%y/%m/%d %H:%M:%S"  => 21/12/31 12:54:98
+        "%y-%m-%d %H:%M:%S"  => 2021-12-31 24:58:01
+        "%y/%m/%d %H:%M:%S"  => 21/12/31 24:58:01
+        "%y%m%d %H:%M:%S"    => 210319 23:58:50
+        "%Y/%m/%d %H:%M:%S"  => 2021/12/31 12:54:98
+        "%Y-%m-%d %H:%M:%S"  => 2021-12-31 24:58:01
+        "%Y/%m/%d %H:%M:%S"  => 2021/12/31 24:58:01
+        "%Y%m%d %H:%M:%S"    => 20210319 23:58:50
+        "%FT%H:%M:%S"        => 2019-04-18T02:45:55
+        "%FT%H:%M:%S.%6f"    => microseconds
+        "%FT%H:%M:%S.%9f"    => nanoseconds"#
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("format", SyntaxShape::String, "formatting date time string")
+            .switch("not-exact", "the format string may be contained in the date (e.g. foo-2021-01-01-bar could match 2021-01-01)", Some('n'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Converts string to datetime",
+                example: r#"["2021-12-30 00:00:00" "2021-12-31 00:00:00"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S""#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "datetime".to_string(),
+                            vec![
+                                Value::date(
+                                    DateTime::parse_from_str(
+                                        "2021-12-30 00:00:00 +0000",
+                                        "%Y-%m-%d %H:%M:%S %z",
+                                    )
+                                    .expect("date calculation should not fail in test"),
+                                    Span::test_data(),
+                                ),
+                                Value::date(
+                                    DateTime::parse_from_str(
+                                        "2021-12-31 00:00:00 +0000",
+                                        "%Y-%m-%d %H:%M:%S %z",
+                                    )
+                                    .expect("date calculation should not fail in test"),
+                                    Span::test_data(),
+                                ),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Converts string to datetime with high resolutions",
+                example: r#"["2021-12-30 00:00:00.123456789" "2021-12-31 00:00:00.123456789"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S.%9f""#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "datetime".to_string(),
+                            vec![
+                                Value::date(
+                                    DateTime::parse_from_str(
+                                        "2021-12-30 00:00:00.123456789 +0000",
+                                        "%Y-%m-%d %H:%M:%S.%9f %z",
+                                    )
+                                    .expect("date calculation should not fail in test"),
+                                    Span::test_data(),
+                                ),
+                                Value::date(
+                                    DateTime::parse_from_str(
+                                        "2021-12-31 00:00:00.123456789 +0000",
+                                        "%Y-%m-%d %H:%M:%S.%9f %z",
+                                    )
+                                    .expect("date calculation should not fail in test"),
+                                    Span::test_data(),
+                                ),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let format: String = call.req(0)?;
+    let not_exact = call.has_flag("not-exact")?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+    let casted = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error casting to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = if not_exact {
+        casted.as_datetime_not_exact(
+            Some(format.as_str()),
+            TimeUnit::Nanoseconds,
+            false,
+            None,
+            &Default::default(),
+        )
+    } else {
+        casted.as_datetime(
+            Some(format.as_str()),
+            TimeUnit::Nanoseconds,
+            false,
+            false,
+            None,
+            &Default::default(),
+        )
+    };
+
+    let mut res = res
+        .map_err(|e| ShellError::GenericError {
+            error: "Error creating datetime".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+
+    res.rename("datetime");
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&AsDateTime)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_day.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_day.rs
new file mode 100644
index 0000000000..fb0d891640
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_day.rs
@@ -0,0 +1,105 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetDay;
+
+impl PluginCommand for GetDay {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-day"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets day from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns day from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-day"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[4i8, 4]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+
+    fn extra_usage(&self) -> &str {
+        ""
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec![]
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.day().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetDay)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_hour.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_hour.rs
new file mode 100644
index 0000000000..2d658f22aa
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_hour.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetHour;
+
+impl PluginCommand for GetHour {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-hour"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets hour from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns hour from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-hour"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[16i8, 16]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.hour().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetHour)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_minute.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_minute.rs
new file mode 100644
index 0000000000..4a195bba10
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_minute.rs
@@ -0,0 +1,95 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+use polars::{prelude::NamedFrom, series::Series};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::prelude::{DatetimeMethods, IntoSeries};
+
+#[derive(Clone)]
+pub struct GetMinute;
+
+impl PluginCommand for GetMinute {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-minute"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets minute from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns minute from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-minute"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[39i8, 39]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.minute().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetMinute)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_month.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_month.rs
new file mode 100644
index 0000000000..b54fec47ec
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_month.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetMonth;
+
+impl PluginCommand for GetMonth {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-month"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets month from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns month from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-month"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[8i8, 8]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.month().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetMonth)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_nanosecond.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_nanosecond.rs
new file mode 100644
index 0000000000..586bf3304f
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_nanosecond.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetNanosecond;
+
+impl PluginCommand for GetNanosecond {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-nanosecond"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets nanosecond from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns nanosecond from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-nanosecond"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[0i32, 0]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.nanosecond().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetNanosecond)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_ordinal.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_ordinal.rs
new file mode 100644
index 0000000000..0261593cbd
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_ordinal.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetOrdinal;
+
+impl PluginCommand for GetOrdinal {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-ordinal"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets ordinal from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns ordinal from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-ordinal"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[217i16, 217]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.ordinal().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetOrdinal)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_second.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_second.rs
new file mode 100644
index 0000000000..58e4665a44
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_second.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetSecond;
+
+impl PluginCommand for GetSecond {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-second"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets second from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns second from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-second"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[18i8, 18]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.second().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetSecond)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_week.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_week.rs
new file mode 100644
index 0000000000..d19dc8c3f3
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_week.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetWeek;
+
+impl PluginCommand for GetWeek {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-week"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets week from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns week from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-week"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[32i8, 32]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.week().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetWeek)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_weekday.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_weekday.rs
new file mode 100644
index 0000000000..ed66f3a357
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_weekday.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetWeekDay;
+
+impl PluginCommand for GetWeekDay {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-weekday"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets weekday from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns weekday from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-weekday"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[2i8, 2]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.weekday().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetWeekDay)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/get_year.rs b/crates/nu_plugin_polars/src/dataframe/series/date/get_year.rs
new file mode 100644
index 0000000000..7cb548eac0
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/get_year.rs
@@ -0,0 +1,97 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::NuDataFrame;
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type,
+};
+use polars::{
+    prelude::{DatetimeMethods, IntoSeries, NamedFrom},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct GetYear;
+
+impl PluginCommand for GetYear {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars get-year"
+    }
+
+    fn usage(&self) -> &str {
+        "Gets year from date."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns year from a date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars get-year"#,
+            result: Some(
+                NuDataFrame::try_from_series(Series::new("0", &[2020i32, 2020]), Span::test_data())
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to datetime type".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = casted.year().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&GetYear)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/date/mod.rs b/crates/nu_plugin_polars/src/dataframe/series/date/mod.rs
new file mode 100644
index 0000000000..ed3895a172
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/date/mod.rs
@@ -0,0 +1,25 @@
+mod as_date;
+mod as_datetime;
+mod get_day;
+mod get_hour;
+mod get_minute;
+mod get_month;
+mod get_nanosecond;
+mod get_ordinal;
+mod get_second;
+mod get_week;
+mod get_weekday;
+mod get_year;
+
+pub use as_date::AsDate;
+pub use as_datetime::AsDateTime;
+pub use get_day::GetDay;
+pub use get_hour::GetHour;
+pub use get_minute::GetMinute;
+pub use get_month::GetMonth;
+pub use get_nanosecond::GetNanosecond;
+pub use get_ordinal::GetOrdinal;
+pub use get_second::GetSecond;
+pub use get_week::GetWeek;
+pub use get_weekday::GetWeekDay;
+pub use get_year::GetYear;
diff --git a/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_sort.rs b/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_sort.rs
new file mode 100644
index 0000000000..c56deb33ed
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_sort.rs
@@ -0,0 +1,140 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::{IntoSeries, SortOptions};
+
+#[derive(Clone)]
+pub struct ArgSort;
+
+impl PluginCommand for ArgSort {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars arg-sort"
+    }
+
+    fn usage(&self) -> &str {
+        "Returns indexes for a sorted series."
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["argsort", "order", "arrange"]
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .switch("reverse", "reverse order", Some('r'))
+            .switch("nulls-last", "nulls ordered last", Some('n'))
+            .switch(
+                "maintain-order",
+                "maintain order on sorted items",
+                Some('m'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Returns indexes for a sorted series",
+                example: "[1 2 2 3 3] | polars into-df | polars arg-sort",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "arg_sort".to_string(),
+                            vec![
+                                Value::test_int(0),
+                                Value::test_int(1),
+                                Value::test_int(2),
+                                Value::test_int(3),
+                                Value::test_int(4),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Returns indexes for a sorted series",
+                example: "[1 2 2 3 3] | polars into-df | polars arg-sort --reverse",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "arg_sort".to_string(),
+                            vec![
+                                Value::test_int(3),
+                                Value::test_int(4),
+                                Value::test_int(1),
+                                Value::test_int(2),
+                                Value::test_int(0),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let sort_options = SortOptions {
+        descending: call.has_flag("reverse")?,
+        nulls_last: call.has_flag("nulls-last")?,
+        multithreaded: true,
+        maintain_order: call.has_flag("maintain-order")?,
+    };
+
+    let mut res = df
+        .as_series(call.head)?
+        .arg_sort(sort_options)
+        .into_series();
+    res.rename("arg_sort");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ArgSort)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_true.rs b/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_true.rs
new file mode 100644
index 0000000000..d004cb9f7f
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_true.rs
@@ -0,0 +1,126 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::{arg_where, col, IntoLazy};
+
+#[derive(Clone)]
+pub struct ArgTrue;
+
+impl PluginCommand for ArgTrue {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars arg-true"
+    }
+
+    fn usage(&self) -> &str {
+        "Returns indexes where values are true."
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["argtrue", "truth", "boolean-true"]
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns indexes where values are true",
+            example: "[false true false] | polars into-df | polars arg-true",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "arg_true".to_string(),
+                        vec![Value::test_int(1)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let columns = df.as_ref().get_column_names();
+    if columns.len() > 1 {
+        return Err(ShellError::GenericError {
+            error: "Error using as series".into(),
+            msg: "dataframe has more than one column".into(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        });
+    }
+
+    match columns.first() {
+        Some(column) => {
+            let expression = arg_where(col(column).eq(true)).alias("arg_true");
+            let res: NuDataFrame = df
+                .as_ref()
+                .clone()
+                .lazy()
+                .select(&[expression])
+                .collect()
+                .map_err(|err| ShellError::GenericError {
+                    error: "Error creating index column".into(),
+                    msg: err.to_string(),
+                    span: Some(call.head),
+                    help: None,
+                    inner: vec![],
+                })?
+                .into();
+
+            to_pipeline_data(plugin, engine, call.head, res)
+        }
+        _ => Err(ShellError::UnsupportedInput {
+            msg: "Expected the dataframe to have a column".to_string(),
+            input: "".to_string(),
+            msg_span: call.head,
+            input_span: call.head,
+        }),
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ArgTrue)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_unique.rs b/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_unique.rs
new file mode 100644
index 0000000000..92ad4a4952
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/indexes/arg_unique.rs
@@ -0,0 +1,104 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::IntoSeries;
+
+#[derive(Clone)]
+pub struct ArgUnique;
+
+impl PluginCommand for ArgUnique {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars arg-unique"
+    }
+
+    fn usage(&self) -> &str {
+        "Returns indexes for unique values."
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["argunique", "distinct", "noduplicate", "unrepeated"]
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns indexes for unique values",
+            example: "[1 2 2 3 3] | polars into-df | polars arg-unique",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "arg_unique".to_string(),
+                        vec![Value::test_int(0), Value::test_int(1), Value::test_int(3)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let mut res = df
+        .as_series(call.head)?
+        .arg_unique()
+        .map_err(|e| ShellError::GenericError {
+            error: "Error extracting unique values".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+    res.rename("arg_unique");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ArgUnique)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/indexes/mod.rs b/crates/nu_plugin_polars/src/dataframe/series/indexes/mod.rs
new file mode 100644
index 0000000000..c0af8c8653
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/indexes/mod.rs
@@ -0,0 +1,9 @@
+mod arg_sort;
+mod arg_true;
+mod arg_unique;
+mod set_with_idx;
+
+pub use arg_sort::ArgSort;
+pub use arg_true::ArgTrue;
+pub use arg_unique::ArgUnique;
+pub use set_with_idx::SetWithIndex;
diff --git a/crates/nu_plugin_polars/src/dataframe/series/indexes/set_with_idx.rs b/crates/nu_plugin_polars/src/dataframe/series/indexes/set_with_idx.rs
new file mode 100644
index 0000000000..25dc952f23
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/indexes/set_with_idx.rs
@@ -0,0 +1,227 @@
+use crate::{
+    missing_flag_error,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{ChunkSet, DataType, IntoSeries};
+
+#[derive(Clone)]
+pub struct SetWithIndex;
+
+impl PluginCommand for SetWithIndex {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars set-with-idx"
+    }
+
+    fn usage(&self) -> &str {
+        "Sets value in the given index."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("value", SyntaxShape::Any, "value to be inserted in series")
+            .required_named(
+                "indices",
+                SyntaxShape::Any,
+                "list of indices indicating where to set the value",
+                Some('i'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Set value in selected rows from series",
+            example: r#"let series = ([4 1 5 2 4 3] | polars into-df);
+    let indices = ([0 2] | polars into-df);
+    $series | polars set-with-idx 6 --indices $indices"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_int(6),
+                            Value::test_int(1),
+                            Value::test_int(6),
+                            Value::test_int(2),
+                            Value::test_int(4),
+                            Value::test_int(3),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let value: Value = call.req(0)?;
+
+    let indices_value: Value = call
+        .get_flag("indices")?
+        .ok_or_else(|| missing_flag_error("indices", call.head))?;
+
+    let indices_span = indices_value.span();
+    let indices = NuDataFrame::try_from_value_coerce(plugin, &indices_value, call.head)?
+        .as_series(indices_span)?;
+
+    let casted = match indices.dtype() {
+        DataType::UInt32 | DataType::UInt64 | DataType::Int32 | DataType::Int64 => indices
+            .as_ref()
+            .cast(&DataType::UInt32)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error casting indices".into(),
+                msg: e.to_string(),
+                span: Some(indices_span),
+                help: None,
+                inner: vec![],
+            }),
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect type".into(),
+            msg: "Series with incorrect type".into(),
+            span: Some(indices_span),
+            help: Some("Consider using a Series with type int type".into()),
+            inner: vec![],
+        }),
+    }?;
+
+    let indices = casted
+        .u32()
+        .map_err(|e| ShellError::GenericError {
+            error: "Error casting indices".into(),
+            msg: e.to_string(),
+            span: Some(indices_span),
+            help: None,
+            inner: vec![],
+        })?
+        .into_iter()
+        .flatten();
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let span = value.span();
+    let res = match value {
+        Value::Int { val, .. } => {
+            let chunked = series.i64().map_err(|e| ShellError::GenericError {
+                error: "Error casting to i64".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })?;
+
+            let res = chunked.scatter_single(indices, Some(val)).map_err(|e| {
+                ShellError::GenericError {
+                    error: "Error setting value".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }
+            })?;
+
+            NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)
+        }
+        Value::Float { val, .. } => {
+            let chunked = series.f64().map_err(|e| ShellError::GenericError {
+                error: "Error casting to f64".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })?;
+
+            let res = chunked.scatter_single(indices, Some(val)).map_err(|e| {
+                ShellError::GenericError {
+                    error: "Error setting value".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }
+            })?;
+
+            NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)
+        }
+        Value::String { val, .. } => {
+            let chunked = series.str().map_err(|e| ShellError::GenericError {
+                error: "Error casting to string".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })?;
+
+            let res = chunked
+                .scatter_single(indices, Some(val.as_ref()))
+                .map_err(|e| ShellError::GenericError {
+                    error: "Error setting value".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?;
+
+            let mut res = res.into_series();
+            res.rename("string");
+
+            NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect value type".into(),
+            msg: format!(
+                "this value cannot be set in a series of type '{}'",
+                series.dtype()
+            ),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }?;
+
+    to_pipeline_data(plugin, engine, call.head, res)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&SetWithIndex)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/masks/is_duplicated.rs b/crates/nu_plugin_polars/src/dataframe/series/masks/is_duplicated.rs
new file mode 100644
index 0000000000..56cd6e4d70
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/masks/is_duplicated.rs
@@ -0,0 +1,133 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::IntoSeries;
+
+#[derive(Clone)]
+pub struct IsDuplicated;
+
+impl PluginCommand for IsDuplicated {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars is-duplicated"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates mask indicating duplicated values."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create mask indicating duplicated values",
+                example: "[5 6 6 6 8 8 8] | polars into-df | polars is-duplicated",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "is_duplicated".to_string(),
+                            vec![
+                                Value::test_bool(false),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Create mask indicating duplicated rows in a dataframe",
+                example:
+                    "[[a, b]; [1 2] [1 2] [3 3] [3 3] [1 1]] | polars into-df | polars is-duplicated",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "is_duplicated".to_string(),
+                            vec![
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(false),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let mut res = df
+        .as_ref()
+        .is_duplicated()
+        .map_err(|e| ShellError::GenericError {
+            error: "Error finding duplicates".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+
+    res.rename("is_duplicated");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&IsDuplicated)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/masks/is_not_null.rs b/crates/nu_plugin_polars/src/dataframe/series/masks/is_not_null.rs
new file mode 100644
index 0000000000..626e3cb4fa
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/masks/is_not_null.rs
@@ -0,0 +1,130 @@
+use crate::{
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame, NuExpression};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::IntoSeries;
+
+#[derive(Clone)]
+pub struct IsNotNull;
+
+impl PluginCommand for IsNotNull {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars is-not-null"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates mask where value is not null."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create mask where values are not null",
+                example: r#"let s = ([5 6 0 8] | polars into-df);
+    let res = ($s / $s);
+    $res | polars is-not-null"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "is_not_null".to_string(),
+                            vec![
+                                Value::test_bool(true),
+                                Value::test_bool(true),
+                                Value::test_bool(false),
+                                Value::test_bool(true),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates a is not null expression from a column",
+                example: "polars col a | polars is-not-null",
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => {
+                command(plugin, engine, call, lazy.collect(call.head)?)
+            }
+            PolarsPluginObject::NuExpression(expr) => {
+                let expr: NuExpression = expr.to_polars().is_not_null().into();
+                to_pipeline_data(plugin, engine, call.head, expr)
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let mut res = df.as_series(call.head)?.is_not_null();
+    res.rename("is_not_null");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&IsNotNull)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/masks/is_null.rs b/crates/nu_plugin_polars/src/dataframe/series/masks/is_null.rs
new file mode 100644
index 0000000000..5e10d7056c
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/masks/is_null.rs
@@ -0,0 +1,130 @@
+use crate::{
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, NuExpression, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::IntoSeries;
+
+#[derive(Clone)]
+pub struct IsNull;
+
+impl PluginCommand for IsNull {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars is-null"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates mask where value is null."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create mask where values are null",
+                example: r#"let s = ([5 6 0 8] | polars into-df);
+    let res = ($s / $s);
+    $res | polars is-null"#,
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "is_null".to_string(),
+                            vec![
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(true),
+                                Value::test_bool(false),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates a is null expression from a column",
+                example: "polars col a | polars is-null",
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => {
+                command(plugin, engine, call, lazy.collect(call.head)?)
+            }
+            PolarsPluginObject::NuExpression(expr) => {
+                let expr: NuExpression = expr.to_polars().is_null().into();
+                to_pipeline_data(plugin, engine, call.head, expr)
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let mut res = df.as_series(call.head)?.is_null();
+    res.rename("is_null");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&IsNull)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/masks/is_unique.rs b/crates/nu_plugin_polars/src/dataframe/series/masks/is_unique.rs
new file mode 100644
index 0000000000..b2802e8b95
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/masks/is_unique.rs
@@ -0,0 +1,133 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::IntoSeries;
+
+#[derive(Clone)]
+pub struct IsUnique;
+
+impl PluginCommand for IsUnique {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars is-unique"
+    }
+
+    fn usage(&self) -> &str {
+        "Creates mask indicating unique values."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Create mask indicating unique values",
+                example: "[5 6 6 6 8 8 8] | polars into-df | polars is-unique",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "is_unique".to_string(),
+                            vec![
+                                Value::test_bool(true),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Create mask indicating duplicated rows in a dataframe",
+                example:
+                    "[[a, b]; [1 2] [1 2] [3 3] [3 3] [1 1]] | polars into-df | polars is-unique",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "is_unique".to_string(),
+                            vec![
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(false),
+                                Value::test_bool(true),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let mut res = df
+        .as_ref()
+        .is_unique()
+        .map_err(|e| ShellError::GenericError {
+            error: "Error finding unique values".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+
+    res.rename("is_unique");
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&IsUnique)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/masks/mod.rs b/crates/nu_plugin_polars/src/dataframe/series/masks/mod.rs
new file mode 100644
index 0000000000..985b14eaec
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/masks/mod.rs
@@ -0,0 +1,13 @@
+mod is_duplicated;
+mod is_not_null;
+mod is_null;
+mod is_unique;
+mod not;
+mod set;
+
+pub use is_duplicated::IsDuplicated;
+pub use is_not_null::IsNotNull;
+pub use is_null::IsNull;
+pub use is_unique::IsUnique;
+pub use not::NotSeries;
+pub use set::SetSeries;
diff --git a/crates/nu_plugin_polars/src/dataframe/series/masks/not.rs b/crates/nu_plugin_polars/src/dataframe/series/masks/not.rs
new file mode 100644
index 0000000000..5d43714365
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/masks/not.rs
@@ -0,0 +1,103 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::IntoSeries;
+
+use std::ops::Not;
+
+#[derive(Clone)]
+pub struct NotSeries;
+
+impl PluginCommand for NotSeries {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars not"
+    }
+
+    fn usage(&self) -> &str {
+        "Inverts boolean mask."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Inverts boolean mask",
+            example: "[true false true] | polars into-df | polars not",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_bool(false),
+                            Value::test_bool(true),
+                            Value::test_bool(false),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+        command(plugin, engine, call, df).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let series = df.as_series(call.head)?;
+
+    let bool = series.bool().map_err(|e| ShellError::GenericError {
+        error: "Error inverting mask".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = bool.not();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&NotSeries)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/masks/set.rs b/crates/nu_plugin_polars/src/dataframe/series/masks/set.rs
new file mode 100644
index 0000000000..3172af46c3
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/masks/set.rs
@@ -0,0 +1,210 @@
+use crate::{
+    missing_flag_error,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{ChunkSet, DataType, IntoSeries};
+
+#[derive(Clone)]
+pub struct SetSeries;
+
+impl PluginCommand for SetSeries {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars set"
+    }
+
+    fn usage(&self) -> &str {
+        "Sets value where given mask is true."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("value", SyntaxShape::Any, "value to be inserted in series")
+            .required_named(
+                "mask",
+                SyntaxShape::Any,
+                "mask indicating insertions",
+                Some('m'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Shifts the values by a given period",
+            example: r#"let s = ([1 2 2 3 3] | polars into-df | polars shift 2);
+    let mask = ($s | polars is-null);
+    $s | polars set 0 --mask $mask"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_int(0),
+                            Value::test_int(0),
+                            Value::test_int(1),
+                            Value::test_int(2),
+                            Value::test_int(2),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let value: Value = call.req(0)?;
+
+    let mask_value: Value = call
+        .get_flag("mask")?
+        .ok_or_else(|| missing_flag_error("mask", call.head))?;
+
+    let mask_span = mask_value.span();
+    let mask =
+        NuDataFrame::try_from_value_coerce(plugin, &mask_value, call.head)?.as_series(mask_span)?;
+
+    let bool_mask = match mask.dtype() {
+        DataType::Boolean => mask.bool().map_err(|e| ShellError::GenericError {
+            error: "Error casting to bool".into(),
+            msg: e.to_string(),
+            span: Some(mask_span),
+            help: None,
+            inner: vec![],
+        }),
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect type".into(),
+            msg: "can only use bool series as mask".into(),
+            span: Some(mask_span),
+            help: None,
+            inner: vec![],
+        }),
+    }?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+    let span = value.span();
+    let res = match value {
+        Value::Int { val, .. } => {
+            let chunked = series.i64().map_err(|e| ShellError::GenericError {
+                error: "Error casting to i64".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })?;
+
+            let res = chunked
+                .set(bool_mask, Some(val))
+                .map_err(|e| ShellError::GenericError {
+                    error: "Error setting value".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?;
+
+            NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)
+        }
+        Value::Float { val, .. } => {
+            let chunked = series.f64().map_err(|e| ShellError::GenericError {
+                error: "Error casting to f64".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })?;
+
+            let res = chunked
+                .set(bool_mask, Some(val))
+                .map_err(|e| ShellError::GenericError {
+                    error: "Error setting value".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?;
+
+            NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)
+        }
+        Value::String { val, .. } => {
+            let chunked = series.str().map_err(|e| ShellError::GenericError {
+                error: "Error casting to string".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })?;
+
+            let res = chunked.set(bool_mask, Some(val.as_ref())).map_err(|e| {
+                ShellError::GenericError {
+                    error: "Error setting value".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }
+            })?;
+
+            let mut res = res.into_series();
+            res.rename("string");
+
+            NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect value type".into(),
+            msg: format!(
+                "this value cannot be set in a series of type '{}'",
+                series.dtype()
+            ),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }?;
+
+    to_pipeline_data(plugin, engine, call.head, res)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&SetSeries)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/mod.rs b/crates/nu_plugin_polars/src/dataframe/series/mod.rs
new file mode 100644
index 0000000000..94f28b0801
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/mod.rs
@@ -0,0 +1,85 @@
+mod date;
+pub use date::*;
+
+mod string;
+pub use string::*;
+
+mod masks;
+pub use masks::*;
+
+mod indexes;
+pub use indexes::*;
+
+mod all_false;
+mod all_true;
+mod arg_max;
+mod arg_min;
+mod cumulative;
+mod n_null;
+mod n_unique;
+mod rolling;
+mod shift;
+mod unique;
+mod value_counts;
+
+pub use all_false::AllFalse;
+use nu_plugin::PluginCommand;
+
+use crate::PolarsPlugin;
+pub use all_true::AllTrue;
+pub use arg_max::ArgMax;
+pub use arg_min::ArgMin;
+pub use cumulative::Cumulative;
+pub use n_null::NNull;
+pub use n_unique::NUnique;
+pub use rolling::Rolling;
+pub use shift::Shift;
+pub use unique::Unique;
+pub use value_counts::ValueCount;
+
+pub(crate) fn series_commands() -> Vec<Box<dyn PluginCommand<Plugin = PolarsPlugin>>> {
+    vec![
+        Box::new(AllFalse),
+        Box::new(AllTrue),
+        Box::new(ArgMax),
+        Box::new(ArgMin),
+        Box::new(ArgSort),
+        Box::new(ArgTrue),
+        Box::new(ArgUnique),
+        Box::new(AsDate),
+        Box::new(AsDateTime),
+        Box::new(Concatenate),
+        Box::new(Contains),
+        Box::new(Cumulative),
+        Box::new(GetDay),
+        Box::new(GetHour),
+        Box::new(GetMinute),
+        Box::new(GetMonth),
+        Box::new(GetNanosecond),
+        Box::new(GetOrdinal),
+        Box::new(GetSecond),
+        Box::new(GetWeek),
+        Box::new(GetWeekDay),
+        Box::new(GetYear),
+        Box::new(IsDuplicated),
+        Box::new(IsNotNull),
+        Box::new(IsNull),
+        Box::new(IsUnique),
+        Box::new(NNull),
+        Box::new(NUnique),
+        Box::new(NotSeries),
+        Box::new(Replace),
+        Box::new(ReplaceAll),
+        Box::new(Rolling),
+        Box::new(SetSeries),
+        Box::new(SetWithIndex),
+        Box::new(Shift),
+        Box::new(StrLengths),
+        Box::new(StrSlice),
+        Box::new(StrFTime),
+        Box::new(ToLowerCase),
+        Box::new(ToUpperCase),
+        Box::new(Unique),
+        Box::new(ValueCount),
+    ]
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/n_null.rs b/crates/nu_plugin_polars/src/dataframe/series/n_null.rs
new file mode 100644
index 0000000000..fc934b56fb
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/n_null.rs
@@ -0,0 +1,93 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct NNull;
+
+impl PluginCommand for NNull {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars count-null"
+    }
+
+    fn usage(&self) -> &str {
+        "Counts null values."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Counts null values",
+            example: r#"let s = ([1 1 0 0 3 3 4] | polars into-df);
+    ($s / $s) | polars count-null"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "count_null".to_string(),
+                        vec![Value::test_int(2)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let res = df.as_series(call.head)?.null_count();
+    let value = Value::int(res as i64, call.head);
+
+    let df = NuDataFrame::try_from_columns(
+        vec![Column::new("count_null".to_string(), vec![value])],
+        None,
+    )?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&NNull)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/n_unique.rs b/crates/nu_plugin_polars/src/dataframe/series/n_unique.rs
new file mode 100644
index 0000000000..89cde4cc36
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/n_unique.rs
@@ -0,0 +1,135 @@
+use crate::{
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame, NuExpression};
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+#[derive(Clone)]
+pub struct NUnique;
+
+impl PluginCommand for NUnique {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars n-unique"
+    }
+
+    fn usage(&self) -> &str {
+        "Counts unique values."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_types(vec![
+                (
+                    Type::Custom("expression".into()),
+                    Type::Custom("expression".into()),
+                ),
+                (
+                    Type::Custom("dataframe".into()),
+                    Type::Custom("dataframe".into()),
+                ),
+            ])
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Counts unique values",
+                example: "[1 1 2 2 3 3 4] | polars into-df | polars n-unique",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "count_unique".to_string(),
+                            vec![Value::test_int(4)],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates a is n-unique expression from a column",
+                example: "polars col a | polars n-unique",
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => {
+                command(plugin, engine, call, lazy.collect(call.head)?)
+            }
+            PolarsPluginObject::NuExpression(expr) => {
+                let expr: NuExpression = expr.to_polars().n_unique().into();
+                to_pipeline_data(plugin, engine, call.head, expr)
+            }
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let res = df
+        .as_series(call.head)?
+        .n_unique()
+        .map_err(|e| ShellError::GenericError {
+            error: "Error counting unique values".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let value = Value::int(res as i64, call.head);
+
+    let df = NuDataFrame::try_from_columns(
+        vec![Column::new("count_unique".to_string(), vec![value])],
+        None,
+    )?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&NUnique)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/rolling.rs b/crates/nu_plugin_polars/src/dataframe/series/rolling.rs
new file mode 100644
index 0000000000..a64e6f1e70
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/rolling.rs
@@ -0,0 +1,196 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Spanned,
+    SyntaxShape, Type, Value,
+};
+use polars::prelude::{DataType, Duration, IntoSeries, RollingOptionsImpl, SeriesOpsTime};
+
+enum RollType {
+    Min,
+    Max,
+    Sum,
+    Mean,
+}
+
+impl RollType {
+    fn from_str(roll_type: &str, span: Span) -> Result<Self, ShellError> {
+        match roll_type {
+            "min" => Ok(Self::Min),
+            "max" => Ok(Self::Max),
+            "sum" => Ok(Self::Sum),
+            "mean" => Ok(Self::Mean),
+            _ => Err(ShellError::GenericError {
+                error: "Wrong operation".into(),
+                msg: "Operation not valid for cumulative".into(),
+                span: Some(span),
+                help: Some("Allowed values: min, max, sum, mean".into()),
+                inner: vec![],
+            }),
+        }
+    }
+
+    fn to_str(&self) -> &'static str {
+        match self {
+            RollType::Min => "rolling_min",
+            RollType::Max => "rolling_max",
+            RollType::Sum => "rolling_sum",
+            RollType::Mean => "rolling_mean",
+        }
+    }
+}
+
+#[derive(Clone)]
+pub struct Rolling;
+
+impl PluginCommand for Rolling {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars rolling"
+    }
+
+    fn usage(&self) -> &str {
+        "Rolling calculation for a series."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("type", SyntaxShape::String, "rolling operation")
+            .required("window", SyntaxShape::Int, "Window size for rolling")
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Rolling sum for a series",
+                example: "[1 2 3 4 5] | polars into-df | polars rolling sum 2 | polars drop-nulls",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0_rolling_sum".to_string(),
+                            vec![
+                                Value::test_int(3),
+                                Value::test_int(5),
+                                Value::test_int(7),
+                                Value::test_int(9),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Rolling max for a series",
+                example: "[1 2 3 4 5] | polars into-df | polars rolling max 2 | polars drop-nulls",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0_rolling_max".to_string(),
+                            vec![
+                                Value::test_int(2),
+                                Value::test_int(3),
+                                Value::test_int(4),
+                                Value::test_int(5),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let roll_type: Spanned<String> = call.req(0)?;
+    let window_size: i64 = call.req(1)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    if let DataType::Object(..) = series.dtype() {
+        return Err(ShellError::GenericError {
+            error: "Found object series".into(),
+            msg: "Series of type object cannot be used for rolling operation".into(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        });
+    }
+
+    let roll_type = RollType::from_str(&roll_type.item, roll_type.span)?;
+
+    let rolling_opts = RollingOptionsImpl {
+        window_size: Duration::new(window_size),
+        min_periods: window_size as usize,
+        weights: None,
+        center: false,
+        by: None,
+        closed_window: None,
+        tu: None,
+        tz: None,
+        fn_params: None,
+    };
+    let res = match roll_type {
+        RollType::Max => series.rolling_max(rolling_opts),
+        RollType::Min => series.rolling_min(rolling_opts),
+        RollType::Sum => series.rolling_sum(rolling_opts),
+        RollType::Mean => series.rolling_mean(rolling_opts),
+    };
+
+    let mut res = res.map_err(|e| ShellError::GenericError {
+        error: "Error calculating rolling values".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let name = format!("{}_{}", series.name(), roll_type.to_str());
+    res.rename(&name);
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Rolling)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/shift.rs b/crates/nu_plugin_polars/src/dataframe/series/shift.rs
new file mode 100644
index 0000000000..ee35072f84
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/shift.rs
@@ -0,0 +1,136 @@
+use crate::{
+    dataframe::values::{NuExpression, NuLazyFrame},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+
+use polars_plan::prelude::lit;
+
+#[derive(Clone)]
+pub struct Shift;
+
+impl PluginCommand for Shift {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars shift"
+    }
+
+    fn usage(&self) -> &str {
+        "Shifts the values by a given period."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("period", SyntaxShape::Int, "shift period")
+            .named(
+                "fill",
+                SyntaxShape::Any,
+                "Expression used to fill the null values (lazy df)",
+                Some('f'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe or lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Shifts the values by a given period",
+            example: "[1 2 2 3 3] | polars into-df | polars shift 2 | polars drop-nulls",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![Value::test_int(1), Value::test_int(2), Value::test_int(2)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command_eager(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => command_lazy(plugin, engine, call, lazy),
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyGroupBy,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command_eager(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let period: i64 = call.req(0)?;
+    let series = df.as_series(call.head)?.shift(period);
+
+    let df = NuDataFrame::try_from_series_vec(vec![series], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+fn command_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let shift: i64 = call.req(0)?;
+    let fill: Option<Value> = call.get_flag("fill")?;
+
+    let lazy = lazy.to_polars();
+
+    let lazy: NuLazyFrame = match fill {
+        Some(ref fill) => {
+            let expr = NuExpression::try_from_value(plugin, fill)?.to_polars();
+            lazy.shift_and_fill(lit(shift), expr).into()
+        }
+        None => lazy.shift(shift).into(),
+    };
+
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Shift)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/concatenate.rs b/crates/nu_plugin_polars/src/dataframe/series/string/concatenate.rs
new file mode 100644
index 0000000000..25ecbf01b5
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/concatenate.rs
@@ -0,0 +1,124 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{IntoSeries, StringNameSpaceImpl};
+
+#[derive(Clone)]
+pub struct Concatenate;
+
+impl PluginCommand for Concatenate {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars concatenate"
+    }
+
+    fn usage(&self) -> &str {
+        "Concatenates strings with other array."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "other",
+                SyntaxShape::Any,
+                "Other array with string to be concatenated",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Concatenate string",
+            example: r#"let other = ([za xs cd] | polars into-df);
+    [abc abc abc] | polars into-df | polars concatenate $other"#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_string("abcza"),
+                            Value::test_string("abcxs"),
+                            Value::test_string("abccd"),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+
+    let other: Value = call.req(0)?;
+    let other_span = other.span();
+    let other_df = NuDataFrame::try_from_value_coerce(plugin, &other, other_span)?;
+
+    let other_series = other_df.as_series(other_span)?;
+    let other_chunked = other_series.str().map_err(|e| ShellError::GenericError {
+        error: "The concatenate only with string columns".into(),
+        msg: e.to_string(),
+        span: Some(other_span),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let series = df.as_series(call.head)?;
+    let chunked = series.str().map_err(|e| ShellError::GenericError {
+        error: "The concatenate only with string columns".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let mut res = chunked.concat(other_chunked);
+
+    res.rename(series.name());
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Concatenate)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/contains.rs b/crates/nu_plugin_polars/src/dataframe/series/string/contains.rs
new file mode 100644
index 0000000000..701da87bfc
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/contains.rs
@@ -0,0 +1,117 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{IntoSeries, StringNameSpaceImpl};
+
+#[derive(Clone)]
+pub struct Contains;
+
+impl PluginCommand for Contains {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars contains"
+    }
+
+    fn usage(&self) -> &str {
+        "Checks if a pattern is contained in a string."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required(
+                "pattern",
+                SyntaxShape::String,
+                "Regex pattern to be searched",
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns boolean indicating if pattern was found",
+            example: "[abc acb acb] | polars into-df | polars contains ab",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_bool(true),
+                            Value::test_bool(false),
+                            Value::test_bool(false),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let pattern: String = call.req(0)?;
+
+    let series = df.as_series(call.head)?;
+    let chunked = series.str().map_err(|e| ShellError::GenericError {
+        error: "The contains command only with string columns".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let res = chunked
+        .contains(&pattern, false)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error searching in series".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Contains)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/mod.rs b/crates/nu_plugin_polars/src/dataframe/series/string/mod.rs
new file mode 100644
index 0000000000..f2fa19cbaf
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/mod.rs
@@ -0,0 +1,19 @@
+mod concatenate;
+mod contains;
+mod replace;
+mod replace_all;
+mod str_lengths;
+mod str_slice;
+mod strftime;
+mod to_lowercase;
+mod to_uppercase;
+
+pub use concatenate::Concatenate;
+pub use contains::Contains;
+pub use replace::Replace;
+pub use replace_all::ReplaceAll;
+pub use str_lengths::StrLengths;
+pub use str_slice::StrSlice;
+pub use strftime::StrFTime;
+pub use to_lowercase::ToLowerCase;
+pub use to_uppercase::ToUpperCase;
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/replace.rs b/crates/nu_plugin_polars/src/dataframe/series/string/replace.rs
new file mode 100644
index 0000000000..9a9e02e62c
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/replace.rs
@@ -0,0 +1,132 @@
+use crate::{
+    missing_flag_error,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{IntoSeries, StringNameSpaceImpl};
+
+#[derive(Clone)]
+pub struct Replace;
+
+impl PluginCommand for Replace {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars replace"
+    }
+
+    fn usage(&self) -> &str {
+        "Replace the leftmost (sub)string by a regex pattern."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required_named(
+                "pattern",
+                SyntaxShape::String,
+                "Regex pattern to be matched",
+                Some('p'),
+            )
+            .required_named(
+                "replace",
+                SyntaxShape::String,
+                "replacing string",
+                Some('r'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Replaces string",
+            example: "[abc abc abc] | polars into-df | polars replace --pattern ab --replace AB",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_string("ABc"),
+                            Value::test_string("ABc"),
+                            Value::test_string("ABc"),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let pattern: String = call
+        .get_flag("pattern")?
+        .ok_or_else(|| missing_flag_error("pattern", call.head))?;
+    let replace: String = call
+        .get_flag("replace")?
+        .ok_or_else(|| missing_flag_error("replace", call.head))?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+    let chunked = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error conversion to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let mut res = chunked
+        .replace(&pattern, &replace)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error finding pattern other".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?;
+
+    res.rename(series.name());
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Replace)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/replace_all.rs b/crates/nu_plugin_polars/src/dataframe/series/string/replace_all.rs
new file mode 100644
index 0000000000..5011d936f2
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/replace_all.rs
@@ -0,0 +1,134 @@
+use crate::{
+    missing_flag_error,
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{IntoSeries, StringNameSpaceImpl};
+
+#[derive(Clone)]
+pub struct ReplaceAll;
+
+impl PluginCommand for ReplaceAll {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars replace-all"
+    }
+
+    fn usage(&self) -> &str {
+        "Replace all (sub)strings by a regex pattern."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required_named(
+                "pattern",
+                SyntaxShape::String,
+                "Regex pattern to be matched",
+                Some('p'),
+            )
+            .required_named(
+                "replace",
+                SyntaxShape::String,
+                "replacing string",
+                Some('r'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Replaces string",
+            example:
+                "[abac abac abac] | polars into-df | polars replace-all --pattern a --replace A",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_string("AbAc"),
+                            Value::test_string("AbAc"),
+                            Value::test_string("AbAc"),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine_state: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let pattern: String = call
+        .get_flag("pattern")?
+        .ok_or_else(|| missing_flag_error("pattern", call.head))?;
+    let replace: String = call
+        .get_flag("replace")?
+        .ok_or_else(|| missing_flag_error("replace", call.head))?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+    let chunked = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error conversion to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: None,
+        inner: vec![],
+    })?;
+
+    let mut res =
+        chunked
+            .replace_all(&pattern, &replace)
+            .map_err(|e| ShellError::GenericError {
+                error: "Error finding pattern other".into(),
+                msg: e.to_string(),
+                span: Some(call.head),
+                help: None,
+                inner: vec![],
+            })?;
+
+    res.rename(series.name());
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine_state, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ReplaceAll)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/str_lengths.rs b/crates/nu_plugin_polars/src/dataframe/series/string/str_lengths.rs
new file mode 100644
index 0000000000..28babbb14b
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/str_lengths.rs
@@ -0,0 +1,98 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::{IntoSeries, StringNameSpaceImpl};
+
+#[derive(Clone)]
+pub struct StrLengths;
+
+impl PluginCommand for StrLengths {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars str-lengths"
+    }
+
+    fn usage(&self) -> &str {
+        "Get lengths of all strings."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Returns string lengths",
+            example: "[a ab abc] | polars into-df | polars str-lengths",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![Value::test_int(1), Value::test_int(2), Value::test_int(3)],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let chunked = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error casting to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: Some("The str-lengths command can only be used with string columns".into()),
+        inner: vec![],
+    })?;
+
+    let res = chunked.as_ref().str_len_bytes().into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&StrLengths)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/str_slice.rs b/crates/nu_plugin_polars/src/dataframe/series/string/str_slice.rs
new file mode 100644
index 0000000000..51313935d7
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/str_slice.rs
@@ -0,0 +1,147 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::{
+    prelude::{IntoSeries, NamedFrom, StringNameSpaceImpl},
+    series::Series,
+};
+
+#[derive(Clone)]
+pub struct StrSlice;
+
+impl PluginCommand for StrSlice {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars str-slice"
+    }
+
+    fn usage(&self) -> &str {
+        "Slices the string from the start position until the selected length."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("start", SyntaxShape::Int, "start of slice")
+            .named("length", SyntaxShape::Int, "optional length", Some('l'))
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Creates slices from the strings",
+                example: "[abcded abc321 abc123] | polars into-df | polars str-slice 1 --length 2",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0".to_string(),
+                            vec![
+                                Value::test_string("bc"),
+                                Value::test_string("bc"),
+                                Value::test_string("bc"),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates slices from the strings without length",
+                example: "[abcded abc321 abc123] | polars into-df | polars str-slice 1",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new(
+                            "0".to_string(),
+                            vec![
+                                Value::test_string("bcded"),
+                                Value::test_string("bc321"),
+                                Value::test_string("bc123"),
+                            ],
+                        )],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let start: i64 = call.req(0)?;
+    let start = Series::new("", &[start]);
+
+    let length: Option<i64> = call.get_flag("length")?;
+    let length = match length {
+        Some(v) => Series::new("", &[v as u64]),
+        None => Series::new_null("", 1),
+    };
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let chunked = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error casting to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: Some("The str-slice command can only be used with string columns".into()),
+        inner: vec![],
+    })?;
+
+    let res = chunked
+        .str_slice(&start, &length)
+        .map_err(|e| ShellError::GenericError {
+            error: "Dataframe Error".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .with_name(series.name());
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&StrSlice)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/strftime.rs b/crates/nu_plugin_polars/src/dataframe/series/string/strftime.rs
new file mode 100644
index 0000000000..0171be8544
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/strftime.rs
@@ -0,0 +1,116 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::IntoSeries;
+
+#[derive(Clone)]
+pub struct StrFTime;
+
+impl PluginCommand for StrFTime {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars strftime"
+    }
+
+    fn usage(&self) -> &str {
+        "Formats date based on string rule."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .required("fmt", SyntaxShape::String, "Format rule")
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Formats date",
+            example: r#"let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
+    let df = ([$dt $dt] | polars into-df);
+    $df | polars strftime "%Y/%m/%d""#,
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_string("2020/08/04"),
+                            Value::test_string("2020/08/04"),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let fmt: String = call.req(0)?;
+
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.datetime().map_err(|e| ShellError::GenericError {
+        error: "Error casting to date".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: Some("The str-slice command can only be used with string columns".into()),
+        inner: vec![],
+    })?;
+
+    let res = casted
+        .strftime(&fmt)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error formatting datetime".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&StrFTime)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/to_lowercase.rs b/crates/nu_plugin_polars/src/dataframe/series/string/to_lowercase.rs
new file mode 100644
index 0000000000..7ff59ab2e8
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/to_lowercase.rs
@@ -0,0 +1,103 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::{IntoSeries, StringNameSpaceImpl};
+
+#[derive(Clone)]
+pub struct ToLowerCase;
+
+impl PluginCommand for ToLowerCase {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars lowercase"
+    }
+
+    fn usage(&self) -> &str {
+        "Lowercase the strings in the column."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Modifies strings to lowercase",
+            example: "[Abc aBc abC] | polars into-df | polars lowercase",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_string("abc"),
+                            Value::test_string("abc"),
+                            Value::test_string("abc"),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error casting to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: Some("The str-slice command can only be used with string columns".into()),
+        inner: vec![],
+    })?;
+
+    let mut res = casted.to_lowercase();
+    res.rename(series.name());
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ToLowerCase)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/string/to_uppercase.rs b/crates/nu_plugin_polars/src/dataframe/series/string/to_uppercase.rs
new file mode 100644
index 0000000000..c6913d8427
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/string/to_uppercase.rs
@@ -0,0 +1,107 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+use polars::prelude::{IntoSeries, StringNameSpaceImpl};
+
+#[derive(Clone)]
+pub struct ToUpperCase;
+
+impl PluginCommand for ToUpperCase {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars uppercase"
+    }
+
+    fn usage(&self) -> &str {
+        "Uppercase the strings in the column."
+    }
+
+    fn search_terms(&self) -> Vec<&str> {
+        vec!["capitalize, caps, capital"]
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Modifies strings to uppercase",
+            example: "[Abc aBc abC] | polars into-df | polars uppercase",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![Column::new(
+                        "0".to_string(),
+                        vec![
+                            Value::test_string("ABC"),
+                            Value::test_string("ABC"),
+                            Value::test_string("ABC"),
+                        ],
+                    )],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let casted = series.str().map_err(|e| ShellError::GenericError {
+        error: "Error casting to string".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: Some("The str-slice command can only be used with string columns".into()),
+        inner: vec![],
+    })?;
+
+    let mut res = casted.to_uppercase();
+    res.rename(series.name());
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ToUpperCase)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/unique.rs b/crates/nu_plugin_polars/src/dataframe/series/unique.rs
new file mode 100644
index 0000000000..c95648159d
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/unique.rs
@@ -0,0 +1,163 @@
+use crate::{
+    dataframe::{utils::extract_strings, values::NuLazyFrame},
+    values::{
+        cant_convert_err, to_pipeline_data, CustomValueSupport, PolarsPluginObject,
+        PolarsPluginType,
+    },
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, SyntaxShape, Type,
+    Value,
+};
+use polars::prelude::{IntoSeries, UniqueKeepStrategy};
+
+#[derive(Clone)]
+pub struct Unique;
+
+impl PluginCommand for Unique {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars unique"
+    }
+
+    fn usage(&self) -> &str {
+        "Returns unique values from a dataframe."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .named(
+                "subset",
+                SyntaxShape::Any,
+                "Subset of column(s) to use to maintain rows (lazy df)",
+                Some('s'),
+            )
+            .switch(
+                "last",
+                "Keeps last unique value. Default keeps first value (lazy df)",
+                Some('l'),
+            )
+            .switch(
+                "maintain-order",
+                "Keep the same order as the original DataFrame (lazy df)",
+                Some('k'),
+            )
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe or lazyframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![
+            Example {
+                description: "Returns unique values from a series",
+                example: "[2 2 2 2 2] | polars into-df | polars unique",
+                result: Some(
+                    NuDataFrame::try_from_columns(
+                        vec![Column::new("0".to_string(), vec![Value::test_int(2)])],
+                        None,
+                    )
+                    .expect("simple df for test should not fail")
+                    .into_value(Span::test_data()),
+                ),
+            },
+            Example {
+                description: "Creates a is unique expression from a column",
+                example: "col a | unique",
+                result: None,
+            },
+        ]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        let value = input.into_value(call.head);
+
+        match PolarsPluginObject::try_from_value(plugin, &value)? {
+            PolarsPluginObject::NuDataFrame(df) => command_eager(plugin, engine, call, df),
+            PolarsPluginObject::NuLazyFrame(lazy) => command_lazy(plugin, engine, call, lazy),
+            _ => Err(cant_convert_err(
+                &value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyGroupBy,
+                ],
+            )),
+        }
+        .map_err(LabeledError::from)
+    }
+}
+
+fn command_eager(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    df: NuDataFrame,
+) -> Result<PipelineData, ShellError> {
+    let series = df.as_series(call.head)?;
+
+    let res = series.unique().map_err(|e| ShellError::GenericError {
+        error: "Error calculating unique values".into(),
+        msg: e.to_string(),
+        span: Some(call.head),
+        help: Some("The str-slice command can only be used with string columns".into()),
+        inner: vec![],
+    })?;
+
+    let df = NuDataFrame::try_from_series_vec(vec![res.into_series()], call.head)?;
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+fn command_lazy(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    lazy: NuLazyFrame,
+) -> Result<PipelineData, ShellError> {
+    let last = call.has_flag("last")?;
+    let maintain = call.has_flag("maintain-order")?;
+
+    let subset: Option<Value> = call.get_flag("subset")?;
+    let subset = match subset {
+        Some(value) => Some(extract_strings(value)?),
+        None => None,
+    };
+
+    let strategy = if last {
+        UniqueKeepStrategy::Last
+    } else {
+        UniqueKeepStrategy::First
+    };
+
+    let lazy = lazy.to_polars();
+    let lazy: NuLazyFrame = if maintain {
+        lazy.unique(subset, strategy).into()
+    } else {
+        lazy.unique_stable(subset, strategy).into()
+    };
+    to_pipeline_data(plugin, engine, call.head, lazy)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&Unique)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/series/value_counts.rs b/crates/nu_plugin_polars/src/dataframe/series/value_counts.rs
new file mode 100644
index 0000000000..3fc7978f49
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/series/value_counts.rs
@@ -0,0 +1,105 @@
+use crate::{
+    values::{to_pipeline_data, CustomValueSupport},
+    PolarsPlugin,
+};
+
+use super::super::values::{Column, NuDataFrame};
+
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{
+    Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Type, Value,
+};
+
+use polars::prelude::SeriesMethods;
+
+#[derive(Clone)]
+pub struct ValueCount;
+
+impl PluginCommand for ValueCount {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars value-counts"
+    }
+
+    fn usage(&self) -> &str {
+        "Returns a dataframe with the counts for unique values in series."
+    }
+
+    fn signature(&self) -> Signature {
+        Signature::build(self.name())
+            .input_output_type(
+                Type::Custom("dataframe".into()),
+                Type::Custom("dataframe".into()),
+            )
+            .category(Category::Custom("dataframe".into()))
+    }
+
+    fn examples(&self) -> Vec<Example> {
+        vec![Example {
+            description: "Calculates value counts",
+            example: "[5 5 5 5 6 6] | polars into-df | polars value-counts",
+            result: Some(
+                NuDataFrame::try_from_columns(
+                    vec![
+                        Column::new(
+                            "0".to_string(),
+                            vec![Value::test_int(5), Value::test_int(6)],
+                        ),
+                        Column::new(
+                            "count".to_string(),
+                            vec![Value::test_int(4), Value::test_int(2)],
+                        ),
+                    ],
+                    None,
+                )
+                .expect("simple df for test should not fail")
+                .into_value(Span::test_data()),
+            ),
+        }]
+    }
+
+    fn run(
+        &self,
+        plugin: &Self::Plugin,
+        engine: &EngineInterface,
+        call: &EvaluatedCall,
+        input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        command(plugin, engine, call, input).map_err(LabeledError::from)
+    }
+}
+
+fn command(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    call: &EvaluatedCall,
+    input: PipelineData,
+) -> Result<PipelineData, ShellError> {
+    let df = NuDataFrame::try_from_pipeline_coerce(plugin, input, call.head)?;
+    let series = df.as_series(call.head)?;
+
+    let res = series
+        .value_counts(false, false)
+        .map_err(|e| ShellError::GenericError {
+            error: "Error calculating value counts values".into(),
+            msg: e.to_string(),
+            span: Some(call.head),
+            help: Some("The str-slice command can only be used with string columns".into()),
+            inner: vec![],
+        })?;
+
+    let df: NuDataFrame = res.into();
+    to_pipeline_data(plugin, engine, call.head, df)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::test::test_polars_plugin_command;
+
+    #[test]
+    fn test_examples() -> Result<(), ShellError> {
+        test_polars_plugin_command(&ValueCount)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/stub.rs b/crates/nu_plugin_polars/src/dataframe/stub.rs
new file mode 100644
index 0000000000..7b50d23e4e
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/stub.rs
@@ -0,0 +1,51 @@
+use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
+use nu_protocol::{Category, LabeledError, PipelineData, Signature, Type, Value};
+
+use crate::PolarsPlugin;
+
+#[derive(Clone)]
+pub struct PolarsCmd;
+
+impl PluginCommand for PolarsCmd {
+    type Plugin = PolarsPlugin;
+
+    fn name(&self) -> &str {
+        "polars"
+    }
+
+    fn usage(&self) -> &str {
+        "Operate with data in a dataframe format."
+    }
+
+    fn signature(&self) -> nu_protocol::Signature {
+        Signature::build("polars")
+            .category(Category::Custom("dataframe".into()))
+            .input_output_types(vec![(Type::Nothing, Type::String)])
+    }
+
+    fn extra_usage(&self) -> &str {
+        "You must use one of the following subcommands. Using this command as-is will only produce this help message."
+    }
+
+    fn run(
+        &self,
+        _plugin: &Self::Plugin,
+        _engine: &EngineInterface,
+        call: &EvaluatedCall,
+        _input: PipelineData,
+    ) -> Result<PipelineData, LabeledError> {
+        // todo - find a replacmeent for get_full_help
+        // Ok(Value::string(
+        //     get_full_help(
+        //         &PolarsCmd.signature(),
+        //         &PolarsCmd.examples(),
+        //         engine_state,
+        //         stack,
+        //         self.is_parser_keyword(),
+        //     ),
+        //     call.head,
+        // )
+        // .into_pipeline_data())
+        Ok(PipelineData::Value(Value::nothing(call.head), None))
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/utils.rs b/crates/nu_plugin_polars/src/dataframe/utils.rs
new file mode 100644
index 0000000000..db99d550a9
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/utils.rs
@@ -0,0 +1,16 @@
+use nu_protocol::{FromValue, ShellError, Value};
+
+pub fn extract_strings(value: Value) -> Result<Vec<String>, ShellError> {
+    let span = value.span();
+    match (
+        <String as FromValue>::from_value(value.clone()),
+        <Vec<String> as FromValue>::from_value(value),
+    ) {
+        (Ok(col), Err(_)) => Ok(vec![col]),
+        (Err(_), Ok(cols)) => Ok(cols),
+        _ => Err(ShellError::IncompatibleParametersSingle {
+            msg: "Expected a string or list of strings".into(),
+            span,
+        }),
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/mod.rs b/crates/nu_plugin_polars/src/dataframe/values/mod.rs
new file mode 100644
index 0000000000..6f984c6bf8
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/mod.rs
@@ -0,0 +1,345 @@
+mod nu_dataframe;
+mod nu_expression;
+mod nu_lazyframe;
+mod nu_lazygroupby;
+mod nu_schema;
+mod nu_when;
+pub mod utils;
+
+use std::{cmp::Ordering, fmt};
+
+pub use nu_dataframe::{Axis, Column, NuDataFrame, NuDataFrameCustomValue};
+pub use nu_expression::{NuExpression, NuExpressionCustomValue};
+pub use nu_lazyframe::{NuLazyFrame, NuLazyFrameCustomValue};
+pub use nu_lazygroupby::{NuLazyGroupBy, NuLazyGroupByCustomValue};
+use nu_plugin::EngineInterface;
+use nu_protocol::{ast::Operator, CustomValue, PipelineData, ShellError, Span, Spanned, Value};
+pub use nu_schema::{str_to_dtype, NuSchema};
+pub use nu_when::{NuWhen, NuWhenCustomValue, NuWhenType};
+use uuid::Uuid;
+
+use crate::{Cacheable, PolarsPlugin};
+
+#[derive(Debug, Clone)]
+pub enum PolarsPluginType {
+    NuDataFrame,
+    NuLazyFrame,
+    NuExpression,
+    NuLazyGroupBy,
+    NuWhen,
+}
+
+impl fmt::Display for PolarsPluginType {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        match self {
+            Self::NuDataFrame => write!(f, "NuDataFrame"),
+            Self::NuLazyFrame => write!(f, "NuLazyFrame"),
+            Self::NuExpression => write!(f, "NuExpression"),
+            Self::NuLazyGroupBy => write!(f, "NuLazyGroupBy"),
+            Self::NuWhen => write!(f, "NuWhen"),
+        }
+    }
+}
+
+#[derive(Debug, Clone)]
+pub enum PolarsPluginObject {
+    NuDataFrame(NuDataFrame),
+    NuLazyFrame(NuLazyFrame),
+    NuExpression(NuExpression),
+    NuLazyGroupBy(NuLazyGroupBy),
+    NuWhen(NuWhen),
+}
+
+impl PolarsPluginObject {
+    pub fn try_from_value(
+        plugin: &PolarsPlugin,
+        value: &Value,
+    ) -> Result<PolarsPluginObject, ShellError> {
+        if NuDataFrame::can_downcast(value) {
+            NuDataFrame::try_from_value(plugin, value).map(PolarsPluginObject::NuDataFrame)
+        } else if NuLazyFrame::can_downcast(value) {
+            NuLazyFrame::try_from_value(plugin, value).map(PolarsPluginObject::NuLazyFrame)
+        } else if NuExpression::can_downcast(value) {
+            NuExpression::try_from_value(plugin, value).map(PolarsPluginObject::NuExpression)
+        } else if NuLazyGroupBy::can_downcast(value) {
+            NuLazyGroupBy::try_from_value(plugin, value).map(PolarsPluginObject::NuLazyGroupBy)
+        } else if NuWhen::can_downcast(value) {
+            NuWhen::try_from_value(plugin, value).map(PolarsPluginObject::NuWhen)
+        } else {
+            Err(cant_convert_err(
+                value,
+                &[
+                    PolarsPluginType::NuDataFrame,
+                    PolarsPluginType::NuLazyFrame,
+                    PolarsPluginType::NuExpression,
+                    PolarsPluginType::NuLazyGroupBy,
+                    PolarsPluginType::NuWhen,
+                ],
+            ))
+        }
+    }
+
+    pub fn try_from_pipeline(
+        plugin: &PolarsPlugin,
+        input: PipelineData,
+        span: Span,
+    ) -> Result<Self, ShellError> {
+        let value = input.into_value(span);
+        Self::try_from_value(plugin, &value)
+    }
+
+    pub fn get_type(&self) -> PolarsPluginType {
+        match self {
+            Self::NuDataFrame(_) => PolarsPluginType::NuDataFrame,
+            Self::NuLazyFrame(_) => PolarsPluginType::NuLazyFrame,
+            Self::NuExpression(_) => PolarsPluginType::NuExpression,
+            Self::NuLazyGroupBy(_) => PolarsPluginType::NuLazyGroupBy,
+            Self::NuWhen(_) => PolarsPluginType::NuWhen,
+        }
+    }
+
+    pub fn id(&self) -> Uuid {
+        match self {
+            PolarsPluginObject::NuDataFrame(df) => df.id,
+            PolarsPluginObject::NuLazyFrame(lf) => lf.id,
+            PolarsPluginObject::NuExpression(e) => e.id,
+            PolarsPluginObject::NuLazyGroupBy(lg) => lg.id,
+            PolarsPluginObject::NuWhen(w) => w.id,
+        }
+    }
+}
+
+#[derive(Debug, Clone)]
+pub enum CustomValueType {
+    NuDataFrame(NuDataFrameCustomValue),
+    NuLazyFrame(NuLazyFrameCustomValue),
+    NuExpression(NuExpressionCustomValue),
+    NuLazyGroupBy(NuLazyGroupByCustomValue),
+    NuWhen(NuWhenCustomValue),
+}
+
+impl CustomValueType {
+    pub fn id(&self) -> Uuid {
+        match self {
+            CustomValueType::NuDataFrame(df_cv) => df_cv.id,
+            CustomValueType::NuLazyFrame(lf_cv) => lf_cv.id,
+            CustomValueType::NuExpression(e_cv) => e_cv.id,
+            CustomValueType::NuLazyGroupBy(lg_cv) => lg_cv.id,
+            CustomValueType::NuWhen(w_cv) => w_cv.id,
+        }
+    }
+
+    pub fn try_from_custom_value(val: Box<dyn CustomValue>) -> Result<CustomValueType, ShellError> {
+        if let Some(df_cv) = val.as_any().downcast_ref::<NuDataFrameCustomValue>() {
+            Ok(CustomValueType::NuDataFrame(df_cv.clone()))
+        } else if let Some(lf_cv) = val.as_any().downcast_ref::<NuLazyFrameCustomValue>() {
+            Ok(CustomValueType::NuLazyFrame(lf_cv.clone()))
+        } else if let Some(e_cv) = val.as_any().downcast_ref::<NuExpressionCustomValue>() {
+            Ok(CustomValueType::NuExpression(e_cv.clone()))
+        } else if let Some(lg_cv) = val.as_any().downcast_ref::<NuLazyGroupByCustomValue>() {
+            Ok(CustomValueType::NuLazyGroupBy(lg_cv.clone()))
+        } else if let Some(w_cv) = val.as_any().downcast_ref::<NuWhenCustomValue>() {
+            Ok(CustomValueType::NuWhen(w_cv.clone()))
+        } else {
+            Err(ShellError::CantConvert {
+                to_type: "physical type".into(),
+                from_type: "value".into(),
+                span: Span::unknown(),
+                help: None,
+            })
+        }
+    }
+}
+
+pub fn cant_convert_err(value: &Value, types: &[PolarsPluginType]) -> ShellError {
+    let type_string = types
+        .iter()
+        .map(ToString::to_string)
+        .collect::<Vec<String>>()
+        .join(", ");
+
+    ShellError::CantConvert {
+        to_type: type_string,
+        from_type: value.get_type().to_string(),
+        span: value.span(),
+        help: None,
+    }
+}
+
+pub trait PolarsPluginCustomValue: CustomValue {
+    type PolarsPluginObjectType: Clone;
+
+    fn id(&self) -> &Uuid;
+
+    fn internal(&self) -> &Option<Self::PolarsPluginObjectType>;
+
+    fn custom_value_to_base_value(
+        &self,
+        plugin: &PolarsPlugin,
+        engine: &EngineInterface,
+    ) -> Result<Value, ShellError>;
+
+    fn custom_value_operation(
+        &self,
+        _plugin: &PolarsPlugin,
+        _engine: &EngineInterface,
+        _lhs_span: Span,
+        operator: Spanned<Operator>,
+        _right: Value,
+    ) -> Result<Value, ShellError> {
+        Err(ShellError::UnsupportedOperator {
+            operator: operator.item,
+            span: operator.span,
+        })
+    }
+
+    fn custom_value_follow_path_int(
+        &self,
+        _plugin: &PolarsPlugin,
+        _engine: &EngineInterface,
+        self_span: Span,
+        _index: Spanned<usize>,
+    ) -> Result<Value, ShellError> {
+        Err(ShellError::IncompatiblePathAccess {
+            type_name: self.type_name(),
+            span: self_span,
+        })
+    }
+
+    fn custom_value_follow_path_string(
+        &self,
+        _plugin: &PolarsPlugin,
+        _engine: &EngineInterface,
+        self_span: Span,
+        _column_name: Spanned<String>,
+    ) -> Result<Value, ShellError> {
+        Err(ShellError::IncompatiblePathAccess {
+            type_name: self.type_name(),
+            span: self_span,
+        })
+    }
+
+    fn custom_value_partial_cmp(
+        &self,
+        _plugin: &PolarsPlugin,
+        _engine: &EngineInterface,
+        _other_value: Value,
+    ) -> Result<Option<Ordering>, ShellError> {
+        Ok(None)
+    }
+}
+
+/// Handles the ability for a PolarsObjectType implementations to convert between
+/// their respective CustValue type.
+/// PolarsPluginObjectType's (NuDataFrame, NuLazyFrame) should
+/// implement this trait.  
+pub trait CustomValueSupport: Cacheable {
+    type CV: PolarsPluginCustomValue<PolarsPluginObjectType = Self> + CustomValue + 'static;
+
+    fn get_type(&self) -> PolarsPluginType {
+        Self::get_type_static()
+    }
+
+    fn get_type_static() -> PolarsPluginType;
+
+    fn custom_value(self) -> Self::CV;
+
+    fn base_value(self, span: Span) -> Result<Value, ShellError>;
+
+    fn into_value(self, span: Span) -> Value {
+        Value::custom(Box::new(self.custom_value()), span)
+    }
+
+    fn try_from_custom_value(plugin: &PolarsPlugin, cv: &Self::CV) -> Result<Self, ShellError> {
+        if let Some(internal) = cv.internal() {
+            Ok(internal.clone())
+        } else {
+            Self::get_cached(plugin, cv.id())?.ok_or_else(|| ShellError::GenericError {
+                error: format!("Dataframe {:?} not found in cache", cv.id()),
+                msg: "".into(),
+                span: None,
+                help: None,
+                inner: vec![],
+            })
+        }
+    }
+
+    fn try_from_value(plugin: &PolarsPlugin, value: &Value) -> Result<Self, ShellError> {
+        if let Value::Custom { val, .. } = value {
+            if let Some(cv) = val.as_any().downcast_ref::<Self::CV>() {
+                Self::try_from_custom_value(plugin, cv)
+            } else {
+                Err(ShellError::CantConvert {
+                    to_type: Self::get_type_static().to_string(),
+                    from_type: value.get_type().to_string(),
+                    span: value.span(),
+                    help: None,
+                })
+            }
+        } else {
+            Err(ShellError::CantConvert {
+                to_type: Self::get_type_static().to_string(),
+                from_type: value.get_type().to_string(),
+                span: value.span(),
+                help: None,
+            })
+        }
+    }
+
+    fn try_from_pipeline(
+        plugin: &PolarsPlugin,
+        input: PipelineData,
+        span: Span,
+    ) -> Result<Self, ShellError> {
+        let value = input.into_value(span);
+        Self::try_from_value(plugin, &value)
+    }
+
+    fn can_downcast(value: &Value) -> bool {
+        if let Value::Custom { val, .. } = value {
+            val.as_any().downcast_ref::<Self::CV>().is_some()
+        } else {
+            false
+        }
+    }
+}
+
+/// Wraps the cache and into_value calls.
+/// This function also does mapping back and forth
+/// between lazy and eager values and makes sure they
+/// are cached appropriately.
+pub fn cache_and_to_value(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    span: Span,
+    cv: impl CustomValueSupport,
+) -> Result<Value, ShellError> {
+    match cv.to_cache_value()? {
+        // if it was from a lazy value, make it lazy again
+        PolarsPluginObject::NuDataFrame(df) if df.from_lazy => {
+            let df = df.lazy();
+            Ok(df.cache(plugin, engine)?.into_value(span))
+        }
+        // if it was from an eager value, make it eager again
+        PolarsPluginObject::NuLazyFrame(lf) if lf.from_eager => {
+            let lf = lf.collect(span)?;
+            Ok(lf.cache(plugin, engine)?.into_value(span))
+        }
+        _ => Ok(cv.cache(plugin, engine)?.into_value(span)),
+    }
+}
+
+/// Caches the object, converts it to a it's CustomValue counterpart
+/// And creates a pipeline data object out of it
+#[inline]
+pub fn to_pipeline_data(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    span: Span,
+    cv: impl CustomValueSupport,
+) -> Result<PipelineData, ShellError> {
+    Ok(PipelineData::Value(
+        cache_and_to_value(plugin, engine, span, cv)?,
+        None,
+    ))
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/between_values.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/between_values.rs
new file mode 100644
index 0000000000..df0854ffee
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/between_values.rs
@@ -0,0 +1,889 @@
+use super::{operations::Axis, NuDataFrame};
+use nu_protocol::{
+    ast::{Boolean, Comparison, Math, Operator},
+    span, ShellError, Span, Spanned, Value,
+};
+use num::Zero;
+use polars::prelude::{
+    BooleanType, ChunkCompare, ChunkedArray, DataType, Float64Type, Int64Type, IntoSeries,
+    NumOpsDispatchChecked, PolarsError, Series, StringNameSpaceImpl,
+};
+use std::ops::{Add, BitAnd, BitOr, Div, Mul, Sub};
+
+pub(super) fn between_dataframes(
+    operator: Spanned<Operator>,
+    left: &Value,
+    lhs: &NuDataFrame,
+    right: &Value,
+    rhs: &NuDataFrame,
+) -> Result<NuDataFrame, ShellError> {
+    let operation_span = span(&[left.span(), right.span()]);
+    match operator.item {
+        Operator::Math(Math::Plus) => lhs.append_df(rhs, Axis::Row, operation_span),
+        _ => Err(ShellError::OperatorMismatch {
+            op_span: operator.span,
+            lhs_ty: left.get_type().to_string(),
+            lhs_span: left.span(),
+            rhs_ty: right.get_type().to_string(),
+            rhs_span: right.span(),
+        }),
+    }
+}
+
+pub(super) fn compute_between_series(
+    operator: Spanned<Operator>,
+    left: &Value,
+    lhs: &Series,
+    right: &Value,
+    rhs: &Series,
+) -> Result<NuDataFrame, ShellError> {
+    let operation_span = span(&[left.span(), right.span()]);
+    match operator.item {
+        Operator::Math(Math::Plus) => {
+            let mut res = lhs + rhs;
+            let name = format!("sum_{}_{}", lhs.name(), rhs.name());
+            res.rename(&name);
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Math(Math::Minus) => {
+            let mut res = lhs - rhs;
+            let name = format!("sub_{}_{}", lhs.name(), rhs.name());
+            res.rename(&name);
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Math(Math::Multiply) => {
+            let mut res = lhs * rhs;
+            let name = format!("mul_{}_{}", lhs.name(), rhs.name());
+            res.rename(&name);
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Math(Math::Divide) => {
+            let res = lhs.checked_div(rhs);
+            match res {
+                Ok(mut res) => {
+                    let name = format!("div_{}_{}", lhs.name(), rhs.name());
+                    res.rename(&name);
+                    NuDataFrame::try_from_series(res, operation_span)
+                }
+                Err(e) => Err(ShellError::GenericError {
+                    error: "Division error".into(),
+                    msg: e.to_string(),
+                    span: Some(right.span()),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        }
+        Operator::Comparison(Comparison::Equal) => {
+            let name = format!("eq_{}_{}", lhs.name(), rhs.name());
+            let res = compare_series(lhs, rhs, name.as_str(), right.span(), Series::equal)?;
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Comparison(Comparison::NotEqual) => {
+            let name = format!("neq_{}_{}", lhs.name(), rhs.name());
+            let res = compare_series(lhs, rhs, name.as_str(), right.span(), Series::not_equal)?;
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Comparison(Comparison::LessThan) => {
+            let name = format!("lt_{}_{}", lhs.name(), rhs.name());
+            let res = compare_series(lhs, rhs, name.as_str(), right.span(), Series::lt)?;
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Comparison(Comparison::LessThanOrEqual) => {
+            let name = format!("lte_{}_{}", lhs.name(), rhs.name());
+            let res = compare_series(lhs, rhs, name.as_str(), right.span(), Series::lt_eq)?;
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Comparison(Comparison::GreaterThan) => {
+            let name = format!("gt_{}_{}", lhs.name(), rhs.name());
+            let res = compare_series(lhs, rhs, name.as_str(), right.span(), Series::gt)?;
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Comparison(Comparison::GreaterThanOrEqual) => {
+            let name = format!("gte_{}_{}", lhs.name(), rhs.name());
+            let res = compare_series(lhs, rhs, name.as_str(), right.span(), Series::gt_eq)?;
+            NuDataFrame::try_from_series(res, operation_span)
+        }
+        Operator::Boolean(Boolean::And) => match lhs.dtype() {
+            DataType::Boolean => {
+                let lhs_cast = lhs.bool();
+                let rhs_cast = rhs.bool();
+
+                match (lhs_cast, rhs_cast) {
+                    (Ok(l), Ok(r)) => {
+                        let mut res = l.bitand(r).into_series();
+                        let name = format!("and_{}_{}", lhs.name(), rhs.name());
+                        res.rename(&name);
+                        NuDataFrame::try_from_series(res, operation_span)
+                    }
+                    _ => Err(ShellError::GenericError {
+                        error: "Incompatible types".into(),
+                        msg: "unable to cast to boolean".into(),
+                        span: Some(right.span()),
+                        help: None,
+                        inner: vec![],
+                    }),
+                }
+            }
+            _ => Err(ShellError::IncompatibleParametersSingle {
+                msg: format!(
+                    "Operation {} can only be done with boolean values",
+                    operator.item
+                ),
+                span: operation_span,
+            }),
+        },
+        Operator::Boolean(Boolean::Or) => match lhs.dtype() {
+            DataType::Boolean => {
+                let lhs_cast = lhs.bool();
+                let rhs_cast = rhs.bool();
+
+                match (lhs_cast, rhs_cast) {
+                    (Ok(l), Ok(r)) => {
+                        let mut res = l.bitor(r).into_series();
+                        let name = format!("or_{}_{}", lhs.name(), rhs.name());
+                        res.rename(&name);
+                        NuDataFrame::try_from_series(res, operation_span)
+                    }
+                    _ => Err(ShellError::GenericError {
+                        error: "Incompatible types".into(),
+                        msg: "unable to cast to boolean".into(),
+                        span: Some(right.span()),
+                        help: None,
+                        inner: vec![],
+                    }),
+                }
+            }
+            _ => Err(ShellError::IncompatibleParametersSingle {
+                msg: format!(
+                    "Operation {} can only be done with boolean values",
+                    operator.item
+                ),
+                span: operation_span,
+            }),
+        },
+        _ => Err(ShellError::OperatorMismatch {
+            op_span: operator.span,
+            lhs_ty: left.get_type().to_string(),
+            lhs_span: left.span(),
+            rhs_ty: right.get_type().to_string(),
+            rhs_span: right.span(),
+        }),
+    }
+}
+
+fn compare_series<'s, F>(
+    lhs: &'s Series,
+    rhs: &'s Series,
+    name: &'s str,
+    span: Span,
+    f: F,
+) -> Result<Series, ShellError>
+where
+    F: Fn(&'s Series, &'s Series) -> Result<ChunkedArray<BooleanType>, PolarsError>,
+{
+    let mut res = f(lhs, rhs)
+        .map_err(|e| ShellError::GenericError {
+            error: "Equality error".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        })?
+        .into_series();
+
+    res.rename(name);
+    Ok(res)
+}
+
+pub(super) fn compute_series_single_value(
+    operator: Spanned<Operator>,
+    left: &Value,
+    lhs: &NuDataFrame,
+    right: &Value,
+) -> Result<NuDataFrame, ShellError> {
+    if !lhs.is_series() {
+        return Err(ShellError::OperatorMismatch {
+            op_span: operator.span,
+            lhs_ty: left.get_type().to_string(),
+            lhs_span: left.span(),
+            rhs_ty: right.get_type().to_string(),
+            rhs_span: right.span(),
+        });
+    }
+
+    let lhs_span = left.span();
+    let lhs = lhs.as_series(lhs_span)?;
+
+    match operator.item {
+        Operator::Math(Math::Plus) => match &right {
+            Value::Int { val, .. } => {
+                compute_series_i64(&lhs, *val, <ChunkedArray<Int64Type>>::add, lhs_span)
+            }
+            Value::Float { val, .. } => {
+                compute_series_float(&lhs, *val, <ChunkedArray<Float64Type>>::add, lhs_span)
+            }
+            Value::String { val, .. } => add_string_to_series(&lhs, val, lhs_span),
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Math(Math::Minus) => match &right {
+            Value::Int { val, .. } => {
+                compute_series_i64(&lhs, *val, <ChunkedArray<Int64Type>>::sub, lhs_span)
+            }
+            Value::Float { val, .. } => {
+                compute_series_float(&lhs, *val, <ChunkedArray<Float64Type>>::sub, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Math(Math::Multiply) => match &right {
+            Value::Int { val, .. } => {
+                compute_series_i64(&lhs, *val, <ChunkedArray<Int64Type>>::mul, lhs_span)
+            }
+            Value::Float { val, .. } => {
+                compute_series_float(&lhs, *val, <ChunkedArray<Float64Type>>::mul, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Math(Math::Divide) => {
+            let span = right.span();
+            match &right {
+                Value::Int { val, .. } => {
+                    if *val == 0 {
+                        Err(ShellError::DivisionByZero { span })
+                    } else {
+                        compute_series_i64(&lhs, *val, <ChunkedArray<Int64Type>>::div, lhs_span)
+                    }
+                }
+                Value::Float { val, .. } => {
+                    if val.is_zero() {
+                        Err(ShellError::DivisionByZero { span })
+                    } else {
+                        compute_series_float(&lhs, *val, <ChunkedArray<Float64Type>>::div, lhs_span)
+                    }
+                }
+                _ => Err(ShellError::OperatorMismatch {
+                    op_span: operator.span,
+                    lhs_ty: left.get_type().to_string(),
+                    lhs_span: left.span(),
+                    rhs_ty: right.get_type().to_string(),
+                    rhs_span: right.span(),
+                }),
+            }
+        }
+        Operator::Comparison(Comparison::Equal) => match &right {
+            Value::Int { val, .. } => compare_series_i64(&lhs, *val, ChunkedArray::equal, lhs_span),
+            Value::Float { val, .. } => {
+                compare_series_float(&lhs, *val, ChunkedArray::equal, lhs_span)
+            }
+            Value::String { val, .. } => {
+                let equal_pattern = format!("^{}$", fancy_regex::escape(val));
+                contains_series_pat(&lhs, &equal_pattern, lhs_span)
+            }
+            Value::Date { val, .. } => {
+                compare_series_i64(&lhs, val.timestamp_millis(), ChunkedArray::equal, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Comparison(Comparison::NotEqual) => match &right {
+            Value::Int { val, .. } => {
+                compare_series_i64(&lhs, *val, ChunkedArray::not_equal, lhs_span)
+            }
+            Value::Float { val, .. } => {
+                compare_series_float(&lhs, *val, ChunkedArray::not_equal, lhs_span)
+            }
+            Value::Date { val, .. } => compare_series_i64(
+                &lhs,
+                val.timestamp_millis(),
+                ChunkedArray::not_equal,
+                lhs_span,
+            ),
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Comparison(Comparison::LessThan) => match &right {
+            Value::Int { val, .. } => compare_series_i64(&lhs, *val, ChunkedArray::lt, lhs_span),
+            Value::Float { val, .. } => {
+                compare_series_float(&lhs, *val, ChunkedArray::lt, lhs_span)
+            }
+            Value::Date { val, .. } => {
+                compare_series_i64(&lhs, val.timestamp_millis(), ChunkedArray::lt, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Comparison(Comparison::LessThanOrEqual) => match &right {
+            Value::Int { val, .. } => compare_series_i64(&lhs, *val, ChunkedArray::lt_eq, lhs_span),
+            Value::Float { val, .. } => {
+                compare_series_float(&lhs, *val, ChunkedArray::lt_eq, lhs_span)
+            }
+            Value::Date { val, .. } => {
+                compare_series_i64(&lhs, val.timestamp_millis(), ChunkedArray::lt_eq, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Comparison(Comparison::GreaterThan) => match &right {
+            Value::Int { val, .. } => compare_series_i64(&lhs, *val, ChunkedArray::gt, lhs_span),
+            Value::Float { val, .. } => {
+                compare_series_float(&lhs, *val, ChunkedArray::gt, lhs_span)
+            }
+            Value::Date { val, .. } => {
+                compare_series_i64(&lhs, val.timestamp_millis(), ChunkedArray::gt, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Comparison(Comparison::GreaterThanOrEqual) => match &right {
+            Value::Int { val, .. } => compare_series_i64(&lhs, *val, ChunkedArray::gt_eq, lhs_span),
+            Value::Float { val, .. } => {
+                compare_series_float(&lhs, *val, ChunkedArray::gt_eq, lhs_span)
+            }
+            Value::Date { val, .. } => {
+                compare_series_i64(&lhs, val.timestamp_millis(), ChunkedArray::gt_eq, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        // TODO: update this to do a regex match instead of a simple contains?
+        Operator::Comparison(Comparison::RegexMatch) => match &right {
+            Value::String { val, .. } => contains_series_pat(&lhs, val, lhs_span),
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Comparison(Comparison::StartsWith) => match &right {
+            Value::String { val, .. } => {
+                let starts_with_pattern = format!("^{}", fancy_regex::escape(val));
+                contains_series_pat(&lhs, &starts_with_pattern, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        Operator::Comparison(Comparison::EndsWith) => match &right {
+            Value::String { val, .. } => {
+                let ends_with_pattern = format!("{}$", fancy_regex::escape(val));
+                contains_series_pat(&lhs, &ends_with_pattern, lhs_span)
+            }
+            _ => Err(ShellError::OperatorMismatch {
+                op_span: operator.span,
+                lhs_ty: left.get_type().to_string(),
+                lhs_span: left.span(),
+                rhs_ty: right.get_type().to_string(),
+                rhs_span: right.span(),
+            }),
+        },
+        _ => Err(ShellError::OperatorMismatch {
+            op_span: operator.span,
+            lhs_ty: left.get_type().to_string(),
+            lhs_span: left.span(),
+            rhs_ty: right.get_type().to_string(),
+            rhs_span: right.span(),
+        }),
+    }
+}
+
+fn compute_series_i64<F>(
+    series: &Series,
+    val: i64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(ChunkedArray<Int64Type>, i64) -> ChunkedArray<Int64Type>,
+{
+    match series.dtype() {
+        DataType::UInt32 | DataType::Int32 | DataType::UInt64 => {
+            let to_i64 = series.cast(&DataType::Int64);
+
+            match to_i64 {
+                Ok(series) => {
+                    let casted = series.i64();
+                    compute_casted_i64(casted, val, f, span)
+                }
+                Err(e) => Err(ShellError::GenericError {
+                    error: "Unable to cast to i64".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        }
+        DataType::Int64 => {
+            let casted = series.i64();
+            compute_casted_i64(casted, val, f, span)
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect type".into(),
+            msg: format!(
+                "Series of type {} can not be used for operations with an i64 value",
+                series.dtype()
+            ),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn compute_casted_i64<F>(
+    casted: Result<&ChunkedArray<Int64Type>, PolarsError>,
+    val: i64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(ChunkedArray<Int64Type>, i64) -> ChunkedArray<Int64Type>,
+{
+    match casted {
+        Ok(casted) => {
+            let res = f(casted.clone(), val);
+            let res = res.into_series();
+            NuDataFrame::try_from_series(res, span)
+        }
+        Err(e) => Err(ShellError::GenericError {
+            error: "Unable to cast to i64".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn compute_series_float<F>(
+    series: &Series,
+    val: f64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(ChunkedArray<Float64Type>, f64) -> ChunkedArray<Float64Type>,
+{
+    match series.dtype() {
+        DataType::Float32 => {
+            let to_f64 = series.cast(&DataType::Float64);
+
+            match to_f64 {
+                Ok(series) => {
+                    let casted = series.f64();
+                    compute_casted_f64(casted, val, f, span)
+                }
+                Err(e) => Err(ShellError::GenericError {
+                    error: "Unable to cast to f64".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        }
+        DataType::Float64 => {
+            let casted = series.f64();
+            compute_casted_f64(casted, val, f, span)
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect type".into(),
+            msg: format!(
+                "Series of type {} can not be used for operations with a float value",
+                series.dtype()
+            ),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn compute_casted_f64<F>(
+    casted: Result<&ChunkedArray<Float64Type>, PolarsError>,
+    val: f64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(ChunkedArray<Float64Type>, f64) -> ChunkedArray<Float64Type>,
+{
+    match casted {
+        Ok(casted) => {
+            let res = f(casted.clone(), val);
+            let res = res.into_series();
+            NuDataFrame::try_from_series(res, span)
+        }
+        Err(e) => Err(ShellError::GenericError {
+            error: "Unable to cast to f64".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn compare_series_i64<F>(
+    series: &Series,
+    val: i64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(&ChunkedArray<Int64Type>, i64) -> ChunkedArray<BooleanType>,
+{
+    match series.dtype() {
+        DataType::UInt32 | DataType::Int32 | DataType::UInt64 | DataType::Datetime(_, _) => {
+            let to_i64 = series.cast(&DataType::Int64);
+
+            match to_i64 {
+                Ok(series) => {
+                    let casted = series.i64();
+                    compare_casted_i64(casted, val, f, span)
+                }
+                Err(e) => Err(ShellError::GenericError {
+                    error: "Unable to cast to f64".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        }
+        DataType::Date => {
+            let to_i64 = series.cast(&DataType::Int64);
+
+            match to_i64 {
+                Ok(series) => {
+                    let nanosecs_per_day: i64 = 24 * 60 * 60 * 1_000_000_000;
+                    let casted = series
+                        .i64()
+                        .map(|chunked| chunked.mul(nanosecs_per_day))
+                        .expect("already checked for casting");
+                    compare_casted_i64(Ok(&casted), val, f, span)
+                }
+                Err(e) => Err(ShellError::GenericError {
+                    error: "Unable to cast to f64".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        }
+        DataType::Int64 => {
+            let casted = series.i64();
+            compare_casted_i64(casted, val, f, span)
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect type".into(),
+            msg: format!(
+                "Series of type {} can not be used for operations with an i64 value",
+                series.dtype()
+            ),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn compare_casted_i64<F>(
+    casted: Result<&ChunkedArray<Int64Type>, PolarsError>,
+    val: i64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(&ChunkedArray<Int64Type>, i64) -> ChunkedArray<BooleanType>,
+{
+    match casted {
+        Ok(casted) => {
+            let res = f(casted, val);
+            let res = res.into_series();
+            NuDataFrame::try_from_series(res, span)
+        }
+        Err(e) => Err(ShellError::GenericError {
+            error: "Unable to cast to i64".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn compare_series_float<F>(
+    series: &Series,
+    val: f64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(&ChunkedArray<Float64Type>, f64) -> ChunkedArray<BooleanType>,
+{
+    match series.dtype() {
+        DataType::Float32 => {
+            let to_f64 = series.cast(&DataType::Float64);
+
+            match to_f64 {
+                Ok(series) => {
+                    let casted = series.f64();
+                    compare_casted_f64(casted, val, f, span)
+                }
+                Err(e) => Err(ShellError::GenericError {
+                    error: "Unable to cast to i64".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        }
+        DataType::Float64 => {
+            let casted = series.f64();
+            compare_casted_f64(casted, val, f, span)
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Incorrect type".into(),
+            msg: format!(
+                "Series of type {} can not be used for operations with a float value",
+                series.dtype()
+            ),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn compare_casted_f64<F>(
+    casted: Result<&ChunkedArray<Float64Type>, PolarsError>,
+    val: f64,
+    f: F,
+    span: Span,
+) -> Result<NuDataFrame, ShellError>
+where
+    F: Fn(&ChunkedArray<Float64Type>, f64) -> ChunkedArray<BooleanType>,
+{
+    match casted {
+        Ok(casted) => {
+            let res = f(casted, val);
+            let res = res.into_series();
+            NuDataFrame::try_from_series(res, span)
+        }
+        Err(e) => Err(ShellError::GenericError {
+            error: "Unable to cast to f64".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn contains_series_pat(series: &Series, pat: &str, span: Span) -> Result<NuDataFrame, ShellError> {
+    let casted = series.str();
+    match casted {
+        Ok(casted) => {
+            let res = casted.contains(pat, false);
+
+            match res {
+                Ok(res) => {
+                    let res = res.into_series();
+                    NuDataFrame::try_from_series(res, span)
+                }
+                Err(e) => Err(ShellError::GenericError {
+                    error: "Error using contains".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        }
+        Err(e) => Err(ShellError::GenericError {
+            error: "Unable to cast to string".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn add_string_to_series(series: &Series, pat: &str, span: Span) -> Result<NuDataFrame, ShellError> {
+    let casted = series.str();
+    match casted {
+        Ok(casted) => {
+            let res = casted + pat;
+            let res = res.into_series();
+
+            NuDataFrame::try_from_series(res, span)
+        }
+        Err(e) => Err(ShellError::GenericError {
+            error: "Unable to cast to string".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use nu_protocol::Span;
+    use polars::{prelude::NamedFrom, series::Series};
+
+    use crate::{dataframe::values::NuDataFrame, values::CustomValueSupport};
+
+    #[test]
+    fn test_compute_between_series_comparisons() {
+        let series = Series::new("c", &[1, 2]);
+        let df = NuDataFrame::try_from_series_vec(vec![series], Span::test_data())
+            .expect("should be able to create a simple dataframe");
+
+        let c0 = df
+            .column("c", Span::test_data())
+            .expect("should be able to get column c");
+
+        let c0_series = c0
+            .as_series(Span::test_data())
+            .expect("should be able to get series");
+
+        let c0_value = c0.into_value(Span::test_data());
+
+        let c1 = df
+            .column("c", Span::test_data())
+            .expect("should be able to get column c");
+
+        let c1_series = c1
+            .as_series(Span::test_data())
+            .expect("should be able to get series");
+
+        let c1_value = c1.into_value(Span::test_data());
+
+        let op = Spanned {
+            item: Operator::Comparison(Comparison::NotEqual),
+            span: Span::test_data(),
+        };
+        let result = compute_between_series(op, &c0_value, &c0_series, &c1_value, &c1_series)
+            .expect("compare should not fail");
+        let result = result
+            .as_series(Span::test_data())
+            .expect("should be convert to a series");
+        assert_eq!(result, Series::new("neq_c_c", &[false, false]));
+
+        let op = Spanned {
+            item: Operator::Comparison(Comparison::Equal),
+            span: Span::test_data(),
+        };
+        let result = compute_between_series(op, &c0_value, &c0_series, &c1_value, &c1_series)
+            .expect("compare should not fail");
+        let result = result
+            .as_series(Span::test_data())
+            .expect("should be convert to a series");
+        assert_eq!(result, Series::new("eq_c_c", &[true, true]));
+
+        let op = Spanned {
+            item: Operator::Comparison(Comparison::LessThan),
+            span: Span::test_data(),
+        };
+        let result = compute_between_series(op, &c0_value, &c0_series, &c1_value, &c1_series)
+            .expect("compare should not fail");
+        let result = result
+            .as_series(Span::test_data())
+            .expect("should be convert to a series");
+        assert_eq!(result, Series::new("lt_c_c", &[false, false]));
+
+        let op = Spanned {
+            item: Operator::Comparison(Comparison::LessThanOrEqual),
+            span: Span::test_data(),
+        };
+        let result = compute_between_series(op, &c0_value, &c0_series, &c1_value, &c1_series)
+            .expect("compare should not fail");
+        let result = result
+            .as_series(Span::test_data())
+            .expect("should be convert to a series");
+        assert_eq!(result, Series::new("lte_c_c", &[true, true]));
+
+        let op = Spanned {
+            item: Operator::Comparison(Comparison::GreaterThan),
+            span: Span::test_data(),
+        };
+        let result = compute_between_series(op, &c0_value, &c0_series, &c1_value, &c1_series)
+            .expect("compare should not fail");
+        let result = result
+            .as_series(Span::test_data())
+            .expect("should be convert to a series");
+        assert_eq!(result, Series::new("gt_c_c", &[false, false]));
+
+        let op = Spanned {
+            item: Operator::Comparison(Comparison::GreaterThanOrEqual),
+            span: Span::test_data(),
+        };
+        let result = compute_between_series(op, &c0_value, &c0_series, &c1_value, &c1_series)
+            .expect("compare should not fail");
+        let result = result
+            .as_series(Span::test_data())
+            .expect("should be convert to a series");
+        assert_eq!(result, Series::new("gte_c_c", &[true, true]));
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/conversion.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/conversion.rs
new file mode 100644
index 0000000000..9474e9cb78
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/conversion.rs
@@ -0,0 +1,1437 @@
+use std::ops::{Deref, DerefMut};
+
+use chrono::{DateTime, Duration, FixedOffset, NaiveTime, TimeZone, Utc};
+use chrono_tz::Tz;
+use indexmap::map::{Entry, IndexMap};
+use polars::chunked_array::builder::AnonymousOwnedListBuilder;
+use polars::chunked_array::object::builder::ObjectChunkedBuilder;
+use polars::chunked_array::ChunkedArray;
+use polars::datatypes::AnyValue;
+use polars::export::arrow::Either;
+use polars::prelude::{
+    DataFrame, DataType, DatetimeChunked, Float32Type, Float64Type, Int16Type, Int32Type,
+    Int64Type, Int8Type, IntoSeries, ListBooleanChunkedBuilder, ListBuilderTrait,
+    ListPrimitiveChunkedBuilder, ListStringChunkedBuilder, ListType, NamedFrom, NewChunkedArray,
+    ObjectType, Schema, Series, StructChunked, TemporalMethods, TimeUnit, UInt16Type, UInt32Type,
+    UInt64Type, UInt8Type,
+};
+
+use nu_protocol::{Record, ShellError, Span, Value};
+
+use crate::dataframe::values::NuSchema;
+
+use super::{DataFrameValue, NuDataFrame};
+
+const NANOS_PER_DAY: i64 = 86_400_000_000_000;
+
+// The values capacity is for the size of an  vec.
+// Since this is impossible to determine without traversing every value
+// I just picked one. Since this is for converting back and forth
+// between nushell tables the values shouldn't be too extremely large for
+// practical reasons (~ a few thousand rows).
+const VALUES_CAPACITY: usize = 10;
+
+macro_rules! value_to_primitive {
+    ($value:ident, u8) => {
+        $value.as_i64().map(|v| v as u8)
+    };
+    ($value:ident, u16) => {
+        $value.as_i64().map(|v| v as u16)
+    };
+    ($value:ident, u32) => {
+        $value.as_i64().map(|v| v as u32)
+    };
+    ($value:ident, u64) => {
+        $value.as_i64().map(|v| v as u64)
+    };
+    ($value:ident, i8) => {
+        $value.as_i64().map(|v| v as i8)
+    };
+    ($value:ident, i16) => {
+        $value.as_i64().map(|v| v as i16)
+    };
+    ($value:ident, i32) => {
+        $value.as_i64().map(|v| v as i32)
+    };
+    ($value:ident, i64) => {
+        $value.as_i64()
+    };
+    ($value:ident, f32) => {
+        $value.as_f64().map(|v| v as f32)
+    };
+    ($value:ident, f64) => {
+        $value.as_f64()
+    };
+}
+
+#[derive(Debug)]
+pub struct Column {
+    name: String,
+    values: Vec<Value>,
+}
+
+impl Column {
+    pub fn new(name: String, values: Vec<Value>) -> Self {
+        Self { name, values }
+    }
+
+    pub fn new_empty(name: String) -> Self {
+        Self {
+            name,
+            values: Vec::new(),
+        }
+    }
+
+    pub fn name(&self) -> &str {
+        self.name.as_str()
+    }
+}
+
+impl IntoIterator for Column {
+    type Item = Value;
+    type IntoIter = std::vec::IntoIter<Self::Item>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.values.into_iter()
+    }
+}
+
+impl Deref for Column {
+    type Target = Vec<Value>;
+
+    fn deref(&self) -> &Self::Target {
+        &self.values
+    }
+}
+
+impl DerefMut for Column {
+    fn deref_mut(&mut self) -> &mut Self::Target {
+        &mut self.values
+    }
+}
+
+#[derive(Debug)]
+pub struct TypedColumn {
+    column: Column,
+    column_type: Option<DataType>,
+}
+
+impl TypedColumn {
+    fn new_empty(name: String) -> Self {
+        Self {
+            column: Column::new_empty(name),
+            column_type: None,
+        }
+    }
+}
+
+impl Deref for TypedColumn {
+    type Target = Column;
+
+    fn deref(&self) -> &Self::Target {
+        &self.column
+    }
+}
+
+impl DerefMut for TypedColumn {
+    fn deref_mut(&mut self) -> &mut Self::Target {
+        &mut self.column
+    }
+}
+
+pub type ColumnMap = IndexMap<String, TypedColumn>;
+
+pub fn create_column(
+    series: &Series,
+    from_row: usize,
+    to_row: usize,
+    span: Span,
+) -> Result<Column, ShellError> {
+    let size = to_row - from_row;
+    let values = series_to_values(series, Some(from_row), Some(size), span)?;
+    Ok(Column::new(series.name().into(), values))
+}
+
+// Adds a separator to the vector of values using the column names from the
+// dataframe to create the Values Row
+pub fn add_separator(values: &mut Vec<Value>, df: &DataFrame, span: Span) {
+    let mut record = Record::new();
+
+    record.push("index", Value::string("...", span));
+
+    for name in df.get_column_names() {
+        record.push(name, Value::string("...", span))
+    }
+
+    values.push(Value::record(record, span));
+}
+
+// Inserting the values found in a Value::List or Value::Record
+pub fn insert_record(
+    column_values: &mut ColumnMap,
+    record: Record,
+    maybe_schema: &Option<NuSchema>,
+) -> Result<(), ShellError> {
+    for (col, value) in record {
+        insert_value(value, col, column_values, maybe_schema)?;
+    }
+
+    Ok(())
+}
+
+pub fn insert_value(
+    value: Value,
+    key: String,
+    column_values: &mut ColumnMap,
+    maybe_schema: &Option<NuSchema>,
+) -> Result<(), ShellError> {
+    let col_val = match column_values.entry(key.clone()) {
+        Entry::Vacant(entry) => entry.insert(TypedColumn::new_empty(key.clone())),
+        Entry::Occupied(entry) => entry.into_mut(),
+    };
+
+    // Checking that the type for the value is the same
+    // for the previous value in the column
+    if col_val.values.is_empty() {
+        if let Some(schema) = maybe_schema {
+            if let Some(field) = schema.schema.get_field(&key) {
+                col_val.column_type = Some(field.data_type().clone());
+            }
+        }
+
+        if col_val.column_type.is_none() {
+            col_val.column_type = Some(value_to_data_type(&value));
+        }
+
+        col_val.values.push(value);
+    } else {
+        let prev_value = &col_val.values[col_val.values.len() - 1];
+
+        match (&prev_value, &value) {
+            (Value::Int { .. }, Value::Int { .. })
+            | (Value::Float { .. }, Value::Float { .. })
+            | (Value::String { .. }, Value::String { .. })
+            | (Value::Bool { .. }, Value::Bool { .. })
+            | (Value::Date { .. }, Value::Date { .. })
+            | (Value::Filesize { .. }, Value::Filesize { .. })
+            | (Value::Duration { .. }, Value::Duration { .. }) => col_val.values.push(value),
+            (Value::List { .. }, _) => {
+                col_val.column_type = Some(value_to_data_type(&value));
+                col_val.values.push(value);
+            }
+            _ => {
+                col_val.column_type = Some(DataType::Object("Value", None));
+                col_val.values.push(value);
+            }
+        }
+    }
+
+    Ok(())
+}
+
+fn value_to_data_type(value: &Value) -> DataType {
+    match &value {
+        Value::Int { .. } => DataType::Int64,
+        Value::Float { .. } => DataType::Float64,
+        Value::String { .. } => DataType::String,
+        Value::Bool { .. } => DataType::Boolean,
+        Value::Date { .. } => DataType::Date,
+        Value::Duration { .. } => DataType::Duration(TimeUnit::Nanoseconds),
+        Value::Filesize { .. } => DataType::Int64,
+        Value::List { vals, .. } => {
+            // We need to determined the type inside of the list.
+            // Since Value::List does not have any kind of
+            // type information, we need to look inside the list.
+            // This will cause errors if lists have inconsistent types.
+            // Basically, if a list column needs to be converted to dataframe,
+            // needs to have consistent types.
+            let list_type = vals
+                .iter()
+                .filter(|v| !matches!(v, Value::Nothing { .. }))
+                .map(value_to_data_type)
+                .nth(1)
+                .unwrap_or(DataType::Object("Value", None));
+
+            DataType::List(Box::new(list_type))
+        }
+        _ => DataType::Object("Value", None),
+    }
+}
+
+fn typed_column_to_series(name: &str, column: TypedColumn) -> Result<Series, ShellError> {
+    if let Some(column_type) = &column.column_type {
+        match column_type {
+            DataType::Float32 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_f64().map(|v| v as f32))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::Float64 => {
+                let series_values: Result<Vec<_>, _> =
+                    column.values.iter().map(|v| v.as_f64()).collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::UInt8 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| v as u8))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::UInt16 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| v as u16))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::UInt32 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| v as u32))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::UInt64 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| v as u64))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::Int8 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| v as i8))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::Int16 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| v as i16))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::Int32 => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| v as i32))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::Int64 => {
+                let series_values: Result<Vec<_>, _> =
+                    column.values.iter().map(|v| v.as_i64()).collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::Boolean => {
+                let series_values: Result<Vec<_>, _> =
+                    column.values.iter().map(|v| v.as_bool()).collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::String => {
+                let series_values: Result<Vec<_>, _> =
+                    column.values.iter().map(|v| v.coerce_string()).collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::Object(_, _) => value_to_series(name, &column.values),
+            DataType::Duration(time_unit) => {
+                let series_values: Result<Vec<_>, _> = column
+                    .values
+                    .iter()
+                    .map(|v| v.as_i64().map(|v| nanos_from_timeunit(v, *time_unit)))
+                    .collect();
+                Ok(Series::new(name, series_values?))
+            }
+            DataType::List(list_type) => {
+                match input_type_list_to_series(name, list_type.as_ref(), &column.values) {
+                    Ok(series) => Ok(series),
+                    Err(_) => {
+                        // An error case will occur when there are lists of mixed types.
+                        // If this happens, fallback to object list
+                        input_type_list_to_series(
+                            name,
+                            &DataType::Object("unknown", None),
+                            &column.values,
+                        )
+                    }
+                }
+            }
+            DataType::Date => {
+                let it = column.values.iter().map(|v| {
+                    if let Value::Date { val, .. } = &v {
+                        Some(val.timestamp_nanos_opt().unwrap_or_default())
+                    } else {
+                        None
+                    }
+                });
+
+                let res: DatetimeChunked = ChunkedArray::<Int64Type>::from_iter_options(name, it)
+                    .into_datetime(TimeUnit::Nanoseconds, None);
+
+                Ok(res.into_series())
+            }
+            DataType::Datetime(tu, maybe_tz) => {
+                let dates = column
+                    .values
+                    .iter()
+                    .map(|v| {
+                        if let Value::Date { val, .. } = &v {
+                            // If there is a timezone specified, make sure
+                            // the value is converted to it
+                            Ok(maybe_tz
+                                .as_ref()
+                                .map(|tz| tz.parse::<Tz>().map(|tz| val.with_timezone(&tz)))
+                                .transpose()
+                                .map_err(|e| ShellError::GenericError {
+                                    error: "Error parsing timezone".into(),
+                                    msg: "".into(),
+                                    span: None,
+                                    help: Some(e.to_string()),
+                                    inner: vec![],
+                                })?
+                                .and_then(|dt| dt.timestamp_nanos_opt())
+                                .map(|nanos| nanos_from_timeunit(nanos, *tu)))
+                        } else {
+                            Ok(None)
+                        }
+                    })
+                    .collect::<Result<Vec<Option<i64>>, ShellError>>()?;
+
+                let res: DatetimeChunked =
+                    ChunkedArray::<Int64Type>::from_iter_options(name, dates.into_iter())
+                        .into_datetime(*tu, maybe_tz.clone());
+
+                Ok(res.into_series())
+            }
+            DataType::Struct(fields) => {
+                let schema = Some(NuSchema::new(Schema::from_iter(fields.clone())));
+                let mut structs: Vec<Series> = Vec::new();
+
+                for v in column.values.iter() {
+                    let mut column_values: ColumnMap = IndexMap::new();
+                    let record = v.as_record()?;
+                    insert_record(&mut column_values, record.clone(), &schema)?;
+                    let df = from_parsed_columns(column_values)?;
+                    structs.push(df.as_series(Span::unknown())?);
+                }
+
+                let chunked = StructChunked::new(column.name(), structs.as_ref()).map_err(|e| {
+                    ShellError::GenericError {
+                        error: format!("Error creating struct: {e}"),
+                        msg: "".into(),
+                        span: None,
+                        help: None,
+                        inner: vec![],
+                    }
+                })?;
+                Ok(chunked.into_series())
+            }
+            _ => Err(ShellError::GenericError {
+                error: format!("Error creating dataframe: Unsupported type: {column_type:?}"),
+                msg: "".into(),
+                span: None,
+                help: None,
+                inner: vec![],
+            }),
+        }
+    } else {
+        Err(ShellError::GenericError {
+            error: "Passed a type column with no type".into(),
+            msg: "".into(),
+            span: None,
+            help: None,
+            inner: vec![],
+        })
+    }
+}
+
+// The ColumnMap has the parsed data from the StreamInput
+// This data can be used to create a Series object that can initialize
+// the dataframe based on the type of data that is found
+pub fn from_parsed_columns(column_values: ColumnMap) -> Result<NuDataFrame, ShellError> {
+    let mut df_series: Vec<Series> = Vec::new();
+    for (name, column) in column_values {
+        let series = typed_column_to_series(&name, column)?;
+        df_series.push(series);
+    }
+
+    DataFrame::new(df_series)
+        .map(|df| NuDataFrame::new(false, df))
+        .map_err(|e| ShellError::GenericError {
+            error: "Error creating dataframe".into(),
+            msg: e.to_string(),
+            span: None,
+            help: None,
+            inner: vec![],
+        })
+}
+
+fn value_to_series(name: &str, values: &[Value]) -> Result<Series, ShellError> {
+    let mut builder = ObjectChunkedBuilder::<DataFrameValue>::new(name, values.len());
+
+    for v in values {
+        builder.append_value(DataFrameValue::new(v.clone()));
+    }
+
+    let res = builder.finish();
+    Ok(res.into_series())
+}
+
+fn input_type_list_to_series(
+    name: &str,
+    data_type: &DataType,
+    values: &[Value],
+) -> Result<Series, ShellError> {
+    let inconsistent_error = |_| ShellError::GenericError {
+        error: format!(
+            "column {name} contains a list with inconsistent types: Expecting: {data_type:?}"
+        ),
+        msg: "".into(),
+        span: None,
+        help: None,
+        inner: vec![],
+    };
+
+    macro_rules! primitive_list_series {
+        ($list_type:ty, $vec_type:tt) => {{
+            let mut builder = ListPrimitiveChunkedBuilder::<$list_type>::new(
+                name,
+                values.len(),
+                VALUES_CAPACITY,
+                data_type.clone(),
+            );
+
+            for v in values {
+                let value_list = v
+                    .as_list()?
+                    .iter()
+                    .map(|v| value_to_primitive!(v, $vec_type))
+                    .collect::<Result<Vec<$vec_type>, _>>()
+                    .map_err(inconsistent_error)?;
+                builder.append_iter_values(value_list.iter().copied());
+            }
+            let res = builder.finish();
+            Ok(res.into_series())
+        }};
+    }
+
+    match *data_type {
+        // list of boolean values
+        DataType::Boolean => {
+            let mut builder = ListBooleanChunkedBuilder::new(name, values.len(), VALUES_CAPACITY);
+            for v in values {
+                let value_list = v
+                    .as_list()?
+                    .iter()
+                    .map(|v| v.as_bool())
+                    .collect::<Result<Vec<bool>, _>>()
+                    .map_err(inconsistent_error)?;
+                builder.append_iter(value_list.iter().map(|v| Some(*v)));
+            }
+            let res = builder.finish();
+            Ok(res.into_series())
+        }
+        DataType::Duration(_) => primitive_list_series!(Int64Type, i64),
+        DataType::UInt8 => primitive_list_series!(UInt8Type, u8),
+        DataType::UInt16 => primitive_list_series!(UInt16Type, u16),
+        DataType::UInt32 => primitive_list_series!(UInt32Type, u32),
+        DataType::UInt64 => primitive_list_series!(UInt64Type, u64),
+        DataType::Int8 => primitive_list_series!(Int8Type, i8),
+        DataType::Int16 => primitive_list_series!(Int16Type, i16),
+        DataType::Int32 => primitive_list_series!(Int32Type, i32),
+        DataType::Int64 => primitive_list_series!(Int64Type, i64),
+        DataType::Float32 => primitive_list_series!(Float32Type, f32),
+        DataType::Float64 => primitive_list_series!(Float64Type, f64),
+        DataType::String => {
+            let mut builder = ListStringChunkedBuilder::new(name, values.len(), VALUES_CAPACITY);
+            for v in values {
+                let value_list = v
+                    .as_list()?
+                    .iter()
+                    .map(|v| v.coerce_string())
+                    .collect::<Result<Vec<String>, _>>()
+                    .map_err(inconsistent_error)?;
+                builder.append_values_iter(value_list.iter().map(AsRef::as_ref));
+            }
+            let res = builder.finish();
+            Ok(res.into_series())
+        }
+        DataType::Date => {
+            let mut builder = AnonymousOwnedListBuilder::new(
+                name,
+                values.len(),
+                Some(DataType::Datetime(TimeUnit::Nanoseconds, None)),
+            );
+            for (i, v) in values.iter().enumerate() {
+                let list_name = i.to_string();
+
+                let it = v.as_list()?.iter().map(|v| {
+                    if let Value::Date { val, .. } = &v {
+                        Some(val.timestamp_nanos_opt().unwrap_or_default())
+                    } else {
+                        None
+                    }
+                });
+                let dt_chunked = ChunkedArray::<Int64Type>::from_iter_options(&list_name, it)
+                    .into_datetime(TimeUnit::Nanoseconds, None);
+
+                builder
+                    .append_series(&dt_chunked.into_series())
+                    .map_err(|e| ShellError::GenericError {
+                        error: "Error appending to series".into(),
+                        msg: "".into(),
+                        span: None,
+                        help: Some(e.to_string()),
+                        inner: vec![],
+                    })?
+            }
+            let res = builder.finish();
+            Ok(res.into_series())
+        }
+        DataType::List(ref sub_list_type) => {
+            Ok(input_type_list_to_series(name, sub_list_type, values)?)
+        }
+        // treat everything else as an object
+        _ => Ok(value_to_series(name, values)?),
+    }
+}
+
+fn series_to_values(
+    series: &Series,
+    maybe_from_row: Option<usize>,
+    maybe_size: Option<usize>,
+    span: Span,
+) -> Result<Vec<Value>, ShellError> {
+    match series.dtype() {
+        DataType::Null => {
+            let it = std::iter::repeat(Value::nothing(span));
+            let values = if let Some(size) = maybe_size {
+                Either::Left(it.take(size))
+            } else {
+                Either::Right(it)
+            }
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::UInt8 => {
+            let casted = series.u8().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to u8".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a as i64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::UInt16 => {
+            let casted = series.u16().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to u16".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a as i64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::UInt32 => {
+            let casted = series.u32().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to u32".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a as i64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::UInt64 => {
+            let casted = series.u64().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to u64".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a as i64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Int8 => {
+            let casted = series.i8().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to i8".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a as i64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Int16 => {
+            let casted = series.i16().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to i16".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a as i64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Int32 => {
+            let casted = series.i32().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to i32".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a as i64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Int64 => {
+            let casted = series.i64().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to i64".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::int(a, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Float32 => {
+            let casted = series.f32().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to f32".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::float(a as f64, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Float64 => {
+            let casted = series.f64().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to f64".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::float(a, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Boolean => {
+            let casted = series.bool().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to bool".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::bool(a, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::String => {
+            let casted = series.str().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to string".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => Value::string(a.to_string(), span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        DataType::Object(x, _) => {
+            let casted = series
+                .as_any()
+                .downcast_ref::<ChunkedArray<ObjectType<DataFrameValue>>>();
+
+            match casted {
+                None => Err(ShellError::GenericError {
+                    error: "Error casting object from series".into(),
+                    msg: "".into(),
+                    span: None,
+                    help: Some(format!("Object not supported for conversion: {x}")),
+                    inner: vec![],
+                }),
+                Some(ca) => {
+                    let it = ca.into_iter();
+                    let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row)
+                    {
+                        Either::Left(it.skip(from_row).take(size))
+                    } else {
+                        Either::Right(it)
+                    }
+                    .map(|v| match v {
+                        Some(a) => a.get_value(),
+                        None => Value::nothing(span),
+                    })
+                    .collect::<Vec<Value>>();
+
+                    Ok(values)
+                }
+            }
+        }
+        DataType::List(x) => {
+            let casted = series.as_any().downcast_ref::<ChunkedArray<ListType>>();
+            match casted {
+                None => Err(ShellError::GenericError {
+                    error: "Error casting list from series".into(),
+                    msg: "".into(),
+                    span: None,
+                    help: Some(format!("List not supported for conversion: {x}")),
+                    inner: vec![],
+                }),
+                Some(ca) => {
+                    let it = ca.into_iter();
+                    if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                        Either::Left(it.skip(from_row).take(size))
+                    } else {
+                        Either::Right(it)
+                    }
+                    .map(|ca| {
+                        let sublist: Vec<Value> = if let Some(ref s) = ca {
+                            series_to_values(s, None, None, Span::unknown())?
+                        } else {
+                            // empty item
+                            vec![]
+                        };
+                        Ok(Value::list(sublist, span))
+                    })
+                    .collect::<Result<Vec<Value>, ShellError>>()
+                }
+            }
+        }
+        DataType::Date => {
+            let casted = series.date().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to date".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => {
+                    let nanos = nanos_per_day(a);
+                    let datetime = datetime_from_epoch_nanos(nanos, &None, span)?;
+                    Ok(Value::date(datetime, span))
+                }
+                None => Ok(Value::nothing(span)),
+            })
+            .collect::<Result<Vec<Value>, ShellError>>()?;
+            Ok(values)
+        }
+        DataType::Datetime(time_unit, tz) => {
+            let casted = series.datetime().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to datetime".into(),
+                msg: "".into(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: vec![],
+            })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(a) => {
+                    // elapsed time in nano/micro/milliseconds since 1970-01-01
+                    let nanos = nanos_from_timeunit(a, *time_unit);
+                    let datetime = datetime_from_epoch_nanos(nanos, tz, span)?;
+                    Ok(Value::date(datetime, span))
+                }
+                None => Ok(Value::nothing(span)),
+            })
+            .collect::<Result<Vec<Value>, ShellError>>()?;
+            Ok(values)
+        }
+        DataType::Struct(polar_fields) => {
+            let casted = series.struct_().map_err(|e| ShellError::GenericError {
+                error: "Error casting column to struct".into(),
+                msg: "".to_string(),
+                span: None,
+                help: Some(e.to_string()),
+                inner: Vec::new(),
+            })?;
+            let it = casted.into_iter();
+            let values: Result<Vec<Value>, ShellError> =
+                if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                    Either::Left(it.skip(from_row).take(size))
+                } else {
+                    Either::Right(it)
+                }
+                .map(|any_values| {
+                    let record = polar_fields
+                        .iter()
+                        .zip(any_values)
+                        .map(|(field, val)| {
+                            any_value_to_value(val, span).map(|val| (field.name.to_string(), val))
+                        })
+                        .collect::<Result<_, _>>()?;
+
+                    Ok(Value::record(record, span))
+                })
+                .collect();
+            values
+        }
+        DataType::Time => {
+            let casted =
+                series
+                    .timestamp(TimeUnit::Nanoseconds)
+                    .map_err(|e| ShellError::GenericError {
+                        error: "Error casting column to time".into(),
+                        msg: "".into(),
+                        span: None,
+                        help: Some(e.to_string()),
+                        inner: vec![],
+                    })?;
+
+            let it = casted.into_iter();
+            let values = if let (Some(size), Some(from_row)) = (maybe_size, maybe_from_row) {
+                Either::Left(it.skip(from_row).take(size))
+            } else {
+                Either::Right(it)
+            }
+            .map(|v| match v {
+                Some(nanoseconds) => Value::duration(nanoseconds, span),
+                None => Value::nothing(span),
+            })
+            .collect::<Vec<Value>>();
+
+            Ok(values)
+        }
+        e => Err(ShellError::GenericError {
+            error: "Error creating Dataframe".into(),
+            msg: "".to_string(),
+            span: None,
+            help: Some(format!("Value not supported in nushell: {e}")),
+            inner: vec![],
+        }),
+    }
+}
+
+fn any_value_to_value(any_value: &AnyValue, span: Span) -> Result<Value, ShellError> {
+    match any_value {
+        AnyValue::Null => Ok(Value::nothing(span)),
+        AnyValue::Boolean(b) => Ok(Value::bool(*b, span)),
+        AnyValue::String(s) => Ok(Value::string(s.to_string(), span)),
+        AnyValue::UInt8(i) => Ok(Value::int(*i as i64, span)),
+        AnyValue::UInt16(i) => Ok(Value::int(*i as i64, span)),
+        AnyValue::UInt32(i) => Ok(Value::int(*i as i64, span)),
+        AnyValue::UInt64(i) => Ok(Value::int(*i as i64, span)),
+        AnyValue::Int8(i) => Ok(Value::int(*i as i64, span)),
+        AnyValue::Int16(i) => Ok(Value::int(*i as i64, span)),
+        AnyValue::Int32(i) => Ok(Value::int(*i as i64, span)),
+        AnyValue::Int64(i) => Ok(Value::int(*i, span)),
+        AnyValue::Float32(f) => Ok(Value::float(*f as f64, span)),
+        AnyValue::Float64(f) => Ok(Value::float(*f, span)),
+        AnyValue::Date(d) => {
+            let nanos = nanos_per_day(*d);
+            datetime_from_epoch_nanos(nanos, &None, span)
+                .map(|datetime| Value::date(datetime, span))
+        }
+        AnyValue::Datetime(a, time_unit, tz) => {
+            let nanos = nanos_from_timeunit(*a, *time_unit);
+            datetime_from_epoch_nanos(nanos, tz, span).map(|datetime| Value::date(datetime, span))
+        }
+        AnyValue::Duration(a, time_unit) => {
+            let nanos = match time_unit {
+                TimeUnit::Nanoseconds => *a,
+                TimeUnit::Microseconds => *a * 1_000,
+                TimeUnit::Milliseconds => *a * 1_000_000,
+            };
+            Ok(Value::duration(nanos, span))
+        }
+        // AnyValue::Time represents the current time since midnight.
+        // Unfortunately, there is no timezone related information.
+        // Given this, calculate the current date from UTC and add the time.
+        AnyValue::Time(nanos) => time_from_midnight(*nanos, span),
+        AnyValue::List(series) => {
+            series_to_values(series, None, None, span).map(|values| Value::list(values, span))
+        }
+        AnyValue::Struct(_idx, _struct_array, _s_fields) => {
+            // This should convert to a StructOwned object.
+            let static_value =
+                any_value
+                    .clone()
+                    .into_static()
+                    .map_err(|e| ShellError::GenericError {
+                        error: "Cannot convert polars struct to static value".into(),
+                        msg: e.to_string(),
+                        span: Some(span),
+                        help: None,
+                        inner: Vec::new(),
+                    })?;
+            any_value_to_value(&static_value, span)
+        }
+        AnyValue::StructOwned(struct_tuple) => {
+            let record = struct_tuple
+                .1
+                .iter()
+                .zip(&struct_tuple.0)
+                .map(|(field, val)| {
+                    any_value_to_value(val, span).map(|val| (field.name.to_string(), val))
+                })
+                .collect::<Result<_, _>>()?;
+
+            Ok(Value::record(record, span))
+        }
+        AnyValue::StringOwned(s) => Ok(Value::string(s.to_string(), span)),
+        AnyValue::Binary(bytes) => Ok(Value::binary(*bytes, span)),
+        AnyValue::BinaryOwned(bytes) => Ok(Value::binary(bytes.to_owned(), span)),
+        e => Err(ShellError::GenericError {
+            error: "Error creating Value".into(),
+            msg: "".to_string(),
+            span: None,
+            help: Some(format!("Value not supported in nushell: {e}")),
+            inner: Vec::new(),
+        }),
+    }
+}
+
+fn nanos_per_day(days: i32) -> i64 {
+    days as i64 * NANOS_PER_DAY
+}
+
+fn nanos_from_timeunit(a: i64, time_unit: TimeUnit) -> i64 {
+    a * match time_unit {
+        TimeUnit::Microseconds => 1_000, // Convert microseconds to nanoseconds
+        TimeUnit::Milliseconds => 1_000_000, // Convert milliseconds to nanoseconds
+        TimeUnit::Nanoseconds => 1,      // Already in nanoseconds
+    }
+}
+
+fn datetime_from_epoch_nanos(
+    nanos: i64,
+    timezone: &Option<String>,
+    span: Span,
+) -> Result<DateTime<FixedOffset>, ShellError> {
+    let tz: Tz = if let Some(polars_tz) = timezone {
+        polars_tz
+            .parse::<Tz>()
+            .map_err(|_| ShellError::GenericError {
+                error: format!("Could not parse polars timezone: {polars_tz}"),
+                msg: "".to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })?
+    } else {
+        Tz::UTC
+    };
+
+    Ok(tz.timestamp_nanos(nanos).fixed_offset())
+}
+
+fn time_from_midnight(nanos: i64, span: Span) -> Result<Value, ShellError> {
+    let today = Utc::now().date_naive();
+    NaiveTime::from_hms_opt(0, 0, 0) // midnight
+        .map(|time| time + Duration::nanoseconds(nanos)) // current time
+        .map(|time| today.and_time(time)) // current date and time
+        .and_then(|datetime| {
+            FixedOffset::east_opt(0) // utc
+                .map(|offset| {
+                    DateTime::<FixedOffset>::from_naive_utc_and_offset(datetime, offset)
+                })
+        })
+        .map(|datetime| Value::date(datetime, span)) // current date and time
+        .ok_or(ShellError::CantConvert {
+            to_type: "datetime".to_string(),
+            from_type: "polars time".to_string(),
+            span,
+            help: Some("Could not convert polars time of {nanos} to datetime".to_string()),
+        })
+}
+
+#[cfg(test)]
+mod tests {
+    use indexmap::indexmap;
+    use nu_protocol::record;
+    use polars::export::arrow::array::{BooleanArray, PrimitiveArray};
+    use polars::prelude::Field;
+    use polars_io::prelude::StructArray;
+
+    use super::*;
+
+    #[test]
+    fn test_parsed_column_string_list() -> Result<(), Box<dyn std::error::Error>> {
+        let values = vec![
+            Value::list(
+                vec![Value::string("bar".to_string(), Span::test_data())],
+                Span::test_data(),
+            ),
+            Value::list(
+                vec![Value::string("baz".to_string(), Span::test_data())],
+                Span::test_data(),
+            ),
+        ];
+        let column = Column {
+            name: "foo".to_string(),
+            values: values.clone(),
+        };
+        let typed_column = TypedColumn {
+            column,
+            column_type: Some(DataType::List(Box::new(DataType::String))),
+        };
+
+        let column_map = indexmap!("foo".to_string() => typed_column);
+        let parsed_df = from_parsed_columns(column_map)?;
+        let parsed_columns = parsed_df.columns(Span::test_data())?;
+        assert_eq!(parsed_columns.len(), 1);
+        let column = parsed_columns
+            .first()
+            .expect("There should be a first value in columns");
+        assert_eq!(column.name(), "foo");
+        assert_eq!(column.values, values);
+
+        Ok(())
+    }
+
+    #[test]
+    fn test_any_value_to_value() -> Result<(), Box<dyn std::error::Error>> {
+        let span = Span::test_data();
+        assert_eq!(
+            any_value_to_value(&AnyValue::Null, span)?,
+            Value::nothing(span)
+        );
+
+        let test_bool = true;
+        assert_eq!(
+            any_value_to_value(&AnyValue::Boolean(test_bool), span)?,
+            Value::bool(test_bool, span)
+        );
+
+        let test_str = "foo";
+        assert_eq!(
+            any_value_to_value(&AnyValue::String(test_str), span)?,
+            Value::string(test_str.to_string(), span)
+        );
+        assert_eq!(
+            any_value_to_value(&AnyValue::StringOwned(test_str.into()), span)?,
+            Value::string(test_str.to_owned(), span)
+        );
+
+        let tests_uint8 = 4;
+        assert_eq!(
+            any_value_to_value(&AnyValue::UInt8(tests_uint8), span)?,
+            Value::int(tests_uint8 as i64, span)
+        );
+
+        let tests_uint16 = 233;
+        assert_eq!(
+            any_value_to_value(&AnyValue::UInt16(tests_uint16), span)?,
+            Value::int(tests_uint16 as i64, span)
+        );
+
+        let tests_uint32 = 897688233;
+        assert_eq!(
+            any_value_to_value(&AnyValue::UInt32(tests_uint32), span)?,
+            Value::int(tests_uint32 as i64, span)
+        );
+
+        let tests_uint64 = 903225135897388233;
+        assert_eq!(
+            any_value_to_value(&AnyValue::UInt64(tests_uint64), span)?,
+            Value::int(tests_uint64 as i64, span)
+        );
+
+        let tests_float32 = 903225135897388233.3223353;
+        assert_eq!(
+            any_value_to_value(&AnyValue::Float32(tests_float32), span)?,
+            Value::float(tests_float32 as f64, span)
+        );
+
+        let tests_float64 = 9064251358973882322333.64233533232;
+        assert_eq!(
+            any_value_to_value(&AnyValue::Float64(tests_float64), span)?,
+            Value::float(tests_float64, span)
+        );
+
+        let test_days = 10_957;
+        let comparison_date = Utc
+            .with_ymd_and_hms(2000, 1, 1, 0, 0, 0)
+            .unwrap()
+            .fixed_offset();
+        assert_eq!(
+            any_value_to_value(&AnyValue::Date(test_days), span)?,
+            Value::date(comparison_date, span)
+        );
+
+        let test_millis = 946_684_800_000;
+        assert_eq!(
+            any_value_to_value(
+                &AnyValue::Datetime(test_millis, TimeUnit::Milliseconds, &None),
+                span
+            )?,
+            Value::date(comparison_date, span)
+        );
+
+        let test_duration_millis = 99_999;
+        let test_duration_micros = 99_999_000;
+        let test_duration_nanos = 99_999_000_000;
+        assert_eq!(
+            any_value_to_value(
+                &AnyValue::Duration(test_duration_nanos, TimeUnit::Nanoseconds),
+                span
+            )?,
+            Value::duration(test_duration_nanos, span)
+        );
+        assert_eq!(
+            any_value_to_value(
+                &AnyValue::Duration(test_duration_micros, TimeUnit::Microseconds),
+                span
+            )?,
+            Value::duration(test_duration_nanos, span)
+        );
+        assert_eq!(
+            any_value_to_value(
+                &AnyValue::Duration(test_duration_millis, TimeUnit::Milliseconds),
+                span
+            )?,
+            Value::duration(test_duration_nanos, span)
+        );
+
+        let test_binary = b"sdf2332f32q3f3afwaf3232f32";
+        assert_eq!(
+            any_value_to_value(&AnyValue::Binary(test_binary), span)?,
+            Value::binary(test_binary.to_vec(), span)
+        );
+        assert_eq!(
+            any_value_to_value(&AnyValue::BinaryOwned(test_binary.to_vec()), span)?,
+            Value::binary(test_binary.to_vec(), span)
+        );
+
+        let test_time_nanos = 54_000_000_000_000;
+        let test_time = DateTime::<FixedOffset>::from_naive_utc_and_offset(
+            Utc::now()
+                .date_naive()
+                .and_time(NaiveTime::from_hms_opt(15, 00, 00).unwrap()),
+            FixedOffset::east_opt(0).unwrap(),
+        );
+        assert_eq!(
+            any_value_to_value(&AnyValue::Time(test_time_nanos), span)?,
+            Value::date(test_time, span)
+        );
+
+        let test_list_series = Series::new("int series", &[1, 2, 3]);
+        let comparison_list_series = Value::list(
+            vec![
+                Value::int(1, span),
+                Value::int(2, span),
+                Value::int(3, span),
+            ],
+            span,
+        );
+        assert_eq!(
+            any_value_to_value(&AnyValue::List(test_list_series), span)?,
+            comparison_list_series
+        );
+
+        let field_value_0 = AnyValue::Int32(1);
+        let field_value_1 = AnyValue::Boolean(true);
+        let values = vec![field_value_0, field_value_1];
+        let field_name_0 = "num_field";
+        let field_name_1 = "bool_field";
+        let fields = vec![
+            Field::new(field_name_0, DataType::Int32),
+            Field::new(field_name_1, DataType::Boolean),
+        ];
+        let test_owned_struct = AnyValue::StructOwned(Box::new((values, fields.clone())));
+        let comparison_owned_record = Value::test_record(record!(
+            field_name_0 => Value::int(1, span),
+            field_name_1 => Value::bool(true, span),
+        ));
+        assert_eq!(
+            any_value_to_value(&test_owned_struct, span)?,
+            comparison_owned_record.clone()
+        );
+
+        let test_int_arr = PrimitiveArray::from([Some(1_i32)]);
+        let test_bool_arr = BooleanArray::from([Some(true)]);
+        let test_struct_arr = StructArray::new(
+            DataType::Struct(fields.clone()).to_arrow(true),
+            vec![Box::new(test_int_arr), Box::new(test_bool_arr)],
+            None,
+        );
+        assert_eq!(
+            any_value_to_value(
+                &AnyValue::Struct(0, &test_struct_arr, fields.as_slice()),
+                span
+            )?,
+            comparison_owned_record
+        );
+
+        Ok(())
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/custom_value.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/custom_value.rs
new file mode 100644
index 0000000000..a76683c114
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/custom_value.rs
@@ -0,0 +1,122 @@
+use std::cmp::Ordering;
+
+use nu_plugin::EngineInterface;
+use nu_protocol::{CustomValue, ShellError, Span, Spanned, Value};
+use serde::{Deserialize, Serialize};
+use uuid::Uuid;
+
+use crate::{
+    values::{CustomValueSupport, PolarsPluginCustomValue},
+    Cacheable, PolarsPlugin,
+};
+
+use super::NuDataFrame;
+
+#[derive(Debug, Clone, Deserialize, Serialize)]
+pub struct NuDataFrameCustomValue {
+    pub id: Uuid,
+    #[serde(skip)]
+    pub dataframe: Option<NuDataFrame>,
+}
+
+// CustomValue implementation for NuDataFrame
+#[typetag::serde]
+impl CustomValue for NuDataFrameCustomValue {
+    fn clone_value(&self, span: nu_protocol::Span) -> Value {
+        Value::custom(Box::new(self.clone()), span)
+    }
+
+    fn type_name(&self) -> String {
+        "NuDataFrameCustomValue".into()
+    }
+
+    fn to_base_value(&self, span: Span) -> Result<Value, ShellError> {
+        Ok(Value::string(
+            "NuDataFrameValue: custom_value_to_base_value should've been called",
+            span,
+        ))
+    }
+
+    fn as_mut_any(&mut self) -> &mut dyn std::any::Any {
+        self
+    }
+
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+
+    fn notify_plugin_on_drop(&self) -> bool {
+        true
+    }
+}
+
+impl PolarsPluginCustomValue for NuDataFrameCustomValue {
+    type PolarsPluginObjectType = NuDataFrame;
+
+    fn id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn internal(&self) -> &Option<Self::PolarsPluginObjectType> {
+        &self.dataframe
+    }
+
+    fn custom_value_to_base_value(
+        &self,
+        plugin: &crate::PolarsPlugin,
+        _engine: &nu_plugin::EngineInterface,
+    ) -> Result<Value, ShellError> {
+        let df = NuDataFrame::try_from_custom_value(plugin, self)?;
+        df.base_value(Span::unknown())
+    }
+
+    fn custom_value_operation(
+        &self,
+        plugin: &crate::PolarsPlugin,
+        engine: &nu_plugin::EngineInterface,
+        lhs_span: Span,
+        operator: nu_protocol::Spanned<nu_protocol::ast::Operator>,
+        right: Value,
+    ) -> Result<Value, ShellError> {
+        let df = NuDataFrame::try_from_custom_value(plugin, self)?;
+        Ok(df
+            .compute_with_value(plugin, lhs_span, operator.item, operator.span, &right)?
+            .cache(plugin, engine)?
+            .into_value(lhs_span))
+    }
+
+    fn custom_value_follow_path_int(
+        &self,
+        plugin: &PolarsPlugin,
+        _engine: &EngineInterface,
+        _self_span: Span,
+        index: Spanned<usize>,
+    ) -> Result<Value, ShellError> {
+        let df = NuDataFrame::try_from_custom_value(plugin, self)?;
+        df.get_value(index.item, index.span)
+    }
+
+    fn custom_value_follow_path_string(
+        &self,
+        plugin: &PolarsPlugin,
+        engine: &EngineInterface,
+        self_span: Span,
+        column_name: Spanned<String>,
+    ) -> Result<Value, ShellError> {
+        let df = NuDataFrame::try_from_custom_value(plugin, self)?;
+        let column = df.column(&column_name.item, self_span)?;
+        Ok(column.cache(plugin, engine)?.into_value(self_span))
+    }
+
+    fn custom_value_partial_cmp(
+        &self,
+        plugin: &PolarsPlugin,
+        _engine: &EngineInterface,
+        other_value: Value,
+    ) -> Result<Option<Ordering>, ShellError> {
+        let df = NuDataFrame::try_from_custom_value(plugin, self)?;
+        let other = NuDataFrame::try_from_value_coerce(plugin, &other_value, other_value.span())?;
+        let res = df.is_equal(&other);
+        Ok(res)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/mod.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/mod.rs
new file mode 100644
index 0000000000..ea121994c8
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/mod.rs
@@ -0,0 +1,576 @@
+mod between_values;
+mod conversion;
+mod custom_value;
+mod operations;
+
+pub use conversion::{Column, ColumnMap};
+pub use operations::Axis;
+
+use indexmap::map::IndexMap;
+use nu_protocol::{did_you_mean, PipelineData, Record, ShellError, Span, Value};
+use polars::prelude::{DataFrame, DataType, IntoLazy, PolarsObject, Series};
+use polars_plan::prelude::{lit, Expr, Null};
+use polars_utils::total_ord::TotalEq;
+use std::{cmp::Ordering, collections::HashSet, fmt::Display, hash::Hasher, sync::Arc};
+use uuid::Uuid;
+
+use crate::{Cacheable, PolarsPlugin};
+
+pub use self::custom_value::NuDataFrameCustomValue;
+
+use super::{
+    cant_convert_err, nu_schema::NuSchema, utils::DEFAULT_ROWS, CustomValueSupport, NuLazyFrame,
+    PolarsPluginObject, PolarsPluginType,
+};
+
+// DataFrameValue is an encapsulation of Nushell Value that can be used
+// to define the PolarsObject Trait. The polars object trait allows to
+// create dataframes with mixed datatypes
+#[derive(Clone, Debug)]
+pub struct DataFrameValue(Value);
+
+impl DataFrameValue {
+    fn new(value: Value) -> Self {
+        Self(value)
+    }
+
+    fn get_value(&self) -> Value {
+        self.0.clone()
+    }
+}
+
+impl Display for DataFrameValue {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(f, "{}", self.0.get_type())
+    }
+}
+
+impl Default for DataFrameValue {
+    fn default() -> Self {
+        Self(Value::nothing(Span::unknown()))
+    }
+}
+
+impl PartialEq for DataFrameValue {
+    fn eq(&self, other: &Self) -> bool {
+        self.0.partial_cmp(&other.0).map_or(false, Ordering::is_eq)
+    }
+}
+impl Eq for DataFrameValue {}
+
+impl std::hash::Hash for DataFrameValue {
+    fn hash<H: Hasher>(&self, state: &mut H) {
+        match &self.0 {
+            Value::Nothing { .. } => 0.hash(state),
+            Value::Int { val, .. } => val.hash(state),
+            Value::String { val, .. } => val.hash(state),
+            // TODO. Define hash for the rest of types
+            _ => {}
+        }
+    }
+}
+
+impl TotalEq for DataFrameValue {
+    fn tot_eq(&self, other: &Self) -> bool {
+        self == other
+    }
+}
+
+impl PolarsObject for DataFrameValue {
+    fn type_name() -> &'static str {
+        "object"
+    }
+}
+
+#[derive(Debug, Default, Clone)]
+pub struct NuDataFrame {
+    pub id: Uuid,
+    pub df: Arc<DataFrame>,
+    pub from_lazy: bool,
+}
+
+impl AsRef<DataFrame> for NuDataFrame {
+    fn as_ref(&self) -> &polars::prelude::DataFrame {
+        &self.df
+    }
+}
+
+impl From<DataFrame> for NuDataFrame {
+    fn from(df: DataFrame) -> Self {
+        Self::new(false, df)
+    }
+}
+
+impl NuDataFrame {
+    pub fn new(from_lazy: bool, df: DataFrame) -> Self {
+        let id = Uuid::new_v4();
+        Self {
+            id,
+            df: Arc::new(df),
+            from_lazy,
+        }
+    }
+
+    pub fn to_polars(&self) -> DataFrame {
+        (*self.df).clone()
+    }
+
+    pub fn lazy(&self) -> NuLazyFrame {
+        NuLazyFrame::new(true, self.to_polars().lazy())
+    }
+
+    pub fn try_from_series(series: Series, span: Span) -> Result<Self, ShellError> {
+        match DataFrame::new(vec![series]) {
+            Ok(dataframe) => Ok(NuDataFrame::new(false, dataframe)),
+            Err(e) => Err(ShellError::GenericError {
+                error: "Error creating dataframe".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            }),
+        }
+    }
+
+    pub fn try_from_iter<T>(
+        plugin: &PolarsPlugin,
+        iter: T,
+        maybe_schema: Option<NuSchema>,
+    ) -> Result<Self, ShellError>
+    where
+        T: Iterator<Item = Value>,
+    {
+        // Dictionary to store the columnar data extracted from
+        // the input. During the iteration we check if the values
+        // have different type
+        let mut column_values: ColumnMap = IndexMap::new();
+
+        for value in iter {
+            match value {
+                Value::Custom { .. } => return Self::try_from_value(plugin, &value),
+                Value::List { vals, .. } => {
+                    let record = vals
+                        .into_iter()
+                        .enumerate()
+                        .map(|(i, val)| (format!("{i}"), val))
+                        .collect();
+
+                    conversion::insert_record(&mut column_values, record, &maybe_schema)?
+                }
+                Value::Record { val: record, .. } => {
+                    conversion::insert_record(&mut column_values, *record, &maybe_schema)?
+                }
+                _ => {
+                    let key = "0".to_string();
+                    conversion::insert_value(value, key, &mut column_values, &maybe_schema)?
+                }
+            }
+        }
+
+        let df = conversion::from_parsed_columns(column_values)?;
+        add_missing_columns(df, &maybe_schema, Span::unknown())
+    }
+
+    pub fn try_from_series_vec(columns: Vec<Series>, span: Span) -> Result<Self, ShellError> {
+        let dataframe = DataFrame::new(columns).map_err(|e| ShellError::GenericError {
+            error: "Error creating dataframe".into(),
+            msg: format!("Unable to create DataFrame: {e}"),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        })?;
+
+        Ok(Self::new(false, dataframe))
+    }
+
+    pub fn try_from_columns(
+        columns: Vec<Column>,
+        maybe_schema: Option<NuSchema>,
+    ) -> Result<Self, ShellError> {
+        let mut column_values: ColumnMap = IndexMap::new();
+
+        for column in columns {
+            let name = column.name().to_string();
+            for value in column {
+                conversion::insert_value(value, name.clone(), &mut column_values, &maybe_schema)?;
+            }
+        }
+
+        let df = conversion::from_parsed_columns(column_values)?;
+        add_missing_columns(df, &maybe_schema, Span::unknown())
+    }
+
+    pub fn fill_list_nan(list: Vec<Value>, list_span: Span, fill: Value) -> Value {
+        let newlist = list
+            .into_iter()
+            .map(|value| {
+                let span = value.span();
+                match value {
+                    Value::Float { val, .. } => {
+                        if val.is_nan() {
+                            fill.clone()
+                        } else {
+                            value
+                        }
+                    }
+                    Value::List { vals, .. } => Self::fill_list_nan(vals, span, fill.clone()),
+                    _ => value,
+                }
+            })
+            .collect::<Vec<Value>>();
+        Value::list(newlist, list_span)
+    }
+
+    pub fn columns(&self, span: Span) -> Result<Vec<Column>, ShellError> {
+        let height = self.df.height();
+        self.df
+            .get_columns()
+            .iter()
+            .map(|col| conversion::create_column(col, 0, height, span))
+            .collect::<Result<Vec<Column>, ShellError>>()
+    }
+
+    pub fn column(&self, column: &str, span: Span) -> Result<Self, ShellError> {
+        let s = self.df.column(column).map_err(|_| {
+            let possibilities = self
+                .df
+                .get_column_names()
+                .iter()
+                .map(|name| name.to_string())
+                .collect::<Vec<String>>();
+
+            let option = did_you_mean(&possibilities, column).unwrap_or_else(|| column.to_string());
+            ShellError::DidYouMean {
+                suggestion: option,
+                span,
+            }
+        })?;
+
+        let df = DataFrame::new(vec![s.clone()]).map_err(|e| ShellError::GenericError {
+            error: "Error creating dataframe".into(),
+            msg: e.to_string(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        })?;
+
+        Ok(Self::new(false, df))
+    }
+
+    pub fn is_series(&self) -> bool {
+        self.df.width() == 1
+    }
+
+    pub fn as_series(&self, span: Span) -> Result<Series, ShellError> {
+        if !self.is_series() {
+            return Err(ShellError::GenericError {
+                error: "Error using as series".into(),
+                msg: "dataframe has more than one column".into(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            });
+        }
+
+        let series = self
+            .df
+            .get_columns()
+            .first()
+            .expect("We have already checked that the width is 1");
+
+        Ok(series.clone())
+    }
+
+    pub fn get_value(&self, row: usize, span: Span) -> Result<Value, ShellError> {
+        let series = self.as_series(span)?;
+        let column = conversion::create_column(&series, row, row + 1, span)?;
+
+        if column.len() == 0 {
+            Err(ShellError::AccessEmptyContent { span })
+        } else {
+            let value = column
+                .into_iter()
+                .next()
+                .expect("already checked there is a value");
+            Ok(value)
+        }
+    }
+
+    // Print is made out a head and if the dataframe is too large, then a tail
+    pub fn print(&self, span: Span) -> Result<Vec<Value>, ShellError> {
+        let df = &self.df;
+        let size: usize = 20;
+
+        if df.height() > size {
+            let sample_size = size / 2;
+            let mut values = self.head(Some(sample_size), span)?;
+            conversion::add_separator(&mut values, df, span);
+            let remaining = df.height() - sample_size;
+            let tail_size = remaining.min(sample_size);
+            let mut tail_values = self.tail(Some(tail_size), span)?;
+            values.append(&mut tail_values);
+
+            Ok(values)
+        } else {
+            Ok(self.head(Some(size), span)?)
+        }
+    }
+
+    pub fn height(&self) -> usize {
+        self.df.height()
+    }
+
+    pub fn head(&self, rows: Option<usize>, span: Span) -> Result<Vec<Value>, ShellError> {
+        let to_row = rows.unwrap_or(5);
+        let values = self.to_rows(0, to_row, span)?;
+
+        Ok(values)
+    }
+
+    pub fn tail(&self, rows: Option<usize>, span: Span) -> Result<Vec<Value>, ShellError> {
+        let df = &self.df;
+        let to_row = df.height();
+        let size = rows.unwrap_or(DEFAULT_ROWS);
+        let from_row = to_row.saturating_sub(size);
+
+        let values = self.to_rows(from_row, to_row, span)?;
+
+        Ok(values)
+    }
+
+    pub fn to_rows(
+        &self,
+        from_row: usize,
+        to_row: usize,
+        span: Span,
+    ) -> Result<Vec<Value>, ShellError> {
+        let df = &self.df;
+        let upper_row = to_row.min(df.height());
+
+        let mut size: usize = 0;
+        let columns = self
+            .df
+            .get_columns()
+            .iter()
+            .map(
+                |col| match conversion::create_column(col, from_row, upper_row, span) {
+                    Ok(col) => {
+                        size = col.len();
+                        Ok(col)
+                    }
+                    Err(e) => Err(e),
+                },
+            )
+            .collect::<Result<Vec<Column>, ShellError>>()?;
+
+        let mut iterators = columns
+            .into_iter()
+            .map(|col| (col.name().to_string(), col.into_iter()))
+            .collect::<Vec<(String, std::vec::IntoIter<Value>)>>();
+
+        let values = (0..size)
+            .map(|i| {
+                let mut record = Record::new();
+
+                record.push("index", Value::int((i + from_row) as i64, span));
+
+                for (name, col) in &mut iterators {
+                    record.push(name.clone(), col.next().unwrap_or(Value::nothing(span)));
+                }
+
+                Value::record(record, span)
+            })
+            .collect::<Vec<Value>>();
+
+        Ok(values)
+    }
+
+    // Dataframes are considered equal if they have the same shape, column name and values
+    pub fn is_equal(&self, other: &Self) -> Option<Ordering> {
+        if self.as_ref().width() == 0 {
+            // checking for empty dataframe
+            return None;
+        }
+
+        if self.as_ref().get_column_names() != other.as_ref().get_column_names() {
+            // checking both dataframes share the same names
+            return None;
+        }
+
+        if self.as_ref().height() != other.as_ref().height() {
+            // checking both dataframes have the same row size
+            return None;
+        }
+
+        // sorting dataframe by the first column
+        let column_names = self.as_ref().get_column_names();
+        let first_col = column_names
+            .first()
+            .expect("already checked that dataframe is different than 0");
+
+        // if unable to sort, then unable to compare
+        let lhs = match self.as_ref().sort(vec![*first_col], false, false) {
+            Ok(df) => df,
+            Err(_) => return None,
+        };
+
+        let rhs = match other.as_ref().sort(vec![*first_col], false, false) {
+            Ok(df) => df,
+            Err(_) => return None,
+        };
+
+        for name in self.as_ref().get_column_names() {
+            let self_series = lhs.column(name).expect("name from dataframe names");
+
+            let other_series = rhs
+                .column(name)
+                .expect("already checked that name in other");
+
+            // Casting needed to compare other numeric types with nushell numeric type.
+            // In nushell we only have i64 integer numeric types and any array created
+            // with nushell untagged primitives will be of type i64
+            let self_series = match self_series.dtype() {
+                DataType::UInt32 | DataType::Int32 if *other_series.dtype() == DataType::Int64 => {
+                    match self_series.cast(&DataType::Int64) {
+                        Ok(series) => series,
+                        Err(_) => return None,
+                    }
+                }
+                _ => self_series.clone(),
+            };
+
+            let other_series = match other_series.dtype() {
+                DataType::UInt32 | DataType::Int32 if *self_series.dtype() == DataType::Int64 => {
+                    match other_series.cast(&DataType::Int64) {
+                        Ok(series) => series,
+                        Err(_) => return None,
+                    }
+                }
+                _ => other_series.clone(),
+            };
+
+            if !self_series.equals(&other_series) {
+                return None;
+            }
+        }
+
+        Some(Ordering::Equal)
+    }
+
+    pub fn schema(&self) -> NuSchema {
+        NuSchema::new(self.df.schema())
+    }
+
+    /// This differs from try_from_value as it will attempt to coerce the type into a NuDataFrame.
+    /// So, if the pipeline type is a NuLazyFrame it will be collected and returned as NuDataFrame.
+    pub fn try_from_value_coerce(
+        plugin: &PolarsPlugin,
+        value: &Value,
+        span: Span,
+    ) -> Result<Self, ShellError> {
+        match PolarsPluginObject::try_from_value(plugin, value)? {
+            PolarsPluginObject::NuDataFrame(df) => Ok(df),
+            PolarsPluginObject::NuLazyFrame(lazy) => lazy.collect(span),
+            _ => Err(cant_convert_err(
+                value,
+                &[PolarsPluginType::NuDataFrame, PolarsPluginType::NuLazyFrame],
+            )),
+        }
+    }
+
+    /// This differs from try_from_pipeline as it will attempt to coerce the type into a NuDataFrame.
+    /// So, if the pipeline type is a NuLazyFrame it will be collected and returned as NuDataFrame.
+    pub fn try_from_pipeline_coerce(
+        plugin: &PolarsPlugin,
+        input: PipelineData,
+        span: Span,
+    ) -> Result<Self, ShellError> {
+        let value = input.into_value(span);
+        Self::try_from_value_coerce(plugin, &value, span)
+    }
+}
+
+fn add_missing_columns(
+    df: NuDataFrame,
+    maybe_schema: &Option<NuSchema>,
+    span: Span,
+) -> Result<NuDataFrame, ShellError> {
+    // If there are fields that are in the schema, but not in the dataframe
+    // add them to the dataframe.
+    if let Some(schema) = maybe_schema {
+        let fields = df.df.fields();
+        let df_field_names: HashSet<&str> = fields.iter().map(|f| f.name().as_str()).collect();
+
+        let missing: Vec<(&str, &DataType)> = schema
+            .schema
+            .iter()
+            .filter_map(|(name, dtype)| {
+                let name = name.as_str();
+                if !df_field_names.contains(name) {
+                    Some((name, dtype))
+                } else {
+                    None
+                }
+            })
+            .collect();
+
+        // todo - fix
+        let missing_exprs: Vec<Expr> = missing
+            .iter()
+            .map(|(name, dtype)| lit(Null {}).cast((*dtype).to_owned()).alias(name))
+            .collect();
+
+        let df = if !missing.is_empty() {
+            let lazy: NuLazyFrame = df.lazy().to_polars().with_columns(missing_exprs).into();
+            lazy.collect(span)?
+        } else {
+            df
+        };
+        Ok(df)
+    } else {
+        Ok(df)
+    }
+}
+
+impl Cacheable for NuDataFrame {
+    fn cache_id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn to_cache_value(&self) -> Result<PolarsPluginObject, ShellError> {
+        Ok(PolarsPluginObject::NuDataFrame(self.clone()))
+    }
+
+    fn from_cache_value(cv: PolarsPluginObject) -> Result<Self, ShellError> {
+        match cv {
+            PolarsPluginObject::NuDataFrame(df) => Ok(df),
+            _ => Err(ShellError::GenericError {
+                error: "Cache value is not a dataframe".into(),
+                msg: "".into(),
+                span: None,
+                help: None,
+                inner: vec![],
+            }),
+        }
+    }
+}
+
+impl CustomValueSupport for NuDataFrame {
+    type CV = NuDataFrameCustomValue;
+
+    fn custom_value(self) -> Self::CV {
+        NuDataFrameCustomValue {
+            id: self.id,
+            dataframe: Some(self),
+        }
+    }
+
+    fn base_value(self, span: Span) -> Result<Value, ShellError> {
+        let vals = self.print(span)?;
+        Ok(Value::list(vals, span))
+    }
+
+    fn get_type_static() -> PolarsPluginType {
+        PolarsPluginType::NuDataFrame
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/operations.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/operations.rs
new file mode 100644
index 0000000000..ecdcf73595
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/operations.rs
@@ -0,0 +1,212 @@
+use nu_protocol::{ast::Operator, ShellError, Span, Spanned, Value};
+use polars::prelude::{DataFrame, Series};
+
+use crate::values::CustomValueSupport;
+use crate::PolarsPlugin;
+
+use super::between_values::{
+    between_dataframes, compute_between_series, compute_series_single_value,
+};
+
+use super::NuDataFrame;
+
+pub enum Axis {
+    Row,
+    Column,
+}
+
+impl NuDataFrame {
+    pub fn compute_with_value(
+        &self,
+        plugin: &PolarsPlugin,
+        lhs_span: Span,
+        operator: Operator,
+        op_span: Span,
+        right: &Value,
+    ) -> Result<NuDataFrame, ShellError> {
+        let rhs_span = right.span();
+        match right {
+            Value::Custom { .. } => {
+                let rhs = NuDataFrame::try_from_value(plugin, right)?;
+
+                match (self.is_series(), rhs.is_series()) {
+                    (true, true) => {
+                        let lhs = &self
+                            .as_series(lhs_span)
+                            .expect("Already checked that is a series");
+                        let rhs = &rhs
+                            .as_series(rhs_span)
+                            .expect("Already checked that is a series");
+
+                        if lhs.dtype() != rhs.dtype() {
+                            return Err(ShellError::IncompatibleParameters {
+                                left_message: format!("datatype {}", lhs.dtype()),
+                                left_span: lhs_span,
+                                right_message: format!("datatype {}", lhs.dtype()),
+                                right_span: rhs_span,
+                            });
+                        }
+
+                        if lhs.len() != rhs.len() {
+                            return Err(ShellError::IncompatibleParameters {
+                                left_message: format!("len {}", lhs.len()),
+                                left_span: lhs_span,
+                                right_message: format!("len {}", rhs.len()),
+                                right_span: rhs_span,
+                            });
+                        }
+
+                        let op = Spanned {
+                            item: operator,
+                            span: op_span,
+                        };
+
+                        compute_between_series(
+                            op,
+                            &NuDataFrame::default().into_value(lhs_span),
+                            lhs,
+                            right,
+                            rhs,
+                        )
+                    }
+                    _ => {
+                        if self.df.height() != rhs.df.height() {
+                            return Err(ShellError::IncompatibleParameters {
+                                left_message: format!("rows {}", self.df.height()),
+                                left_span: lhs_span,
+                                right_message: format!("rows {}", rhs.df.height()),
+                                right_span: rhs_span,
+                            });
+                        }
+
+                        let op = Spanned {
+                            item: operator,
+                            span: op_span,
+                        };
+
+                        between_dataframes(
+                            op,
+                            &NuDataFrame::default().into_value(lhs_span),
+                            self,
+                            right,
+                            &rhs,
+                        )
+                    }
+                }
+            }
+            _ => {
+                let op = Spanned {
+                    item: operator,
+                    span: op_span,
+                };
+
+                compute_series_single_value(
+                    op,
+                    &NuDataFrame::default().into_value(lhs_span),
+                    self,
+                    right,
+                )
+            }
+        }
+    }
+
+    pub fn append_df(
+        &self,
+        other: &NuDataFrame,
+        axis: Axis,
+        span: Span,
+    ) -> Result<NuDataFrame, ShellError> {
+        match axis {
+            Axis::Row => {
+                let mut columns: Vec<&str> = Vec::new();
+
+                let new_cols = self
+                    .df
+                    .get_columns()
+                    .iter()
+                    .chain(other.df.get_columns())
+                    .map(|s| {
+                        let name = if columns.contains(&s.name()) {
+                            format!("{}_{}", s.name(), "x")
+                        } else {
+                            columns.push(s.name());
+                            s.name().to_string()
+                        };
+
+                        let mut series = s.clone();
+                        series.rename(&name);
+                        series
+                    })
+                    .collect::<Vec<Series>>();
+
+                let df_new = DataFrame::new(new_cols).map_err(|e| ShellError::GenericError {
+                    error: "Error creating dataframe".into(),
+                    msg: e.to_string(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?;
+
+                Ok(NuDataFrame::new(false, df_new))
+            }
+            Axis::Column => {
+                if self.df.width() != other.df.width() {
+                    return Err(ShellError::IncompatibleParametersSingle {
+                        msg: "Dataframes with different number of columns".into(),
+                        span,
+                    });
+                }
+
+                if !self
+                    .df
+                    .get_column_names()
+                    .iter()
+                    .all(|col| other.df.get_column_names().contains(col))
+                {
+                    return Err(ShellError::IncompatibleParametersSingle {
+                        msg: "Dataframes with different columns names".into(),
+                        span,
+                    });
+                }
+
+                let new_cols = self
+                    .df
+                    .get_columns()
+                    .iter()
+                    .map(|s| {
+                        let other_col = other
+                            .df
+                            .column(s.name())
+                            .expect("Already checked that dataframes have same columns");
+
+                        let mut tmp = s.clone();
+                        let res = tmp.append(other_col);
+
+                        match res {
+                            Ok(s) => Ok(s.clone()),
+                            Err(e) => Err({
+                                ShellError::GenericError {
+                                    error: "Error appending dataframe".into(),
+                                    msg: format!("Unable to append: {e}"),
+                                    span: Some(span),
+                                    help: None,
+                                    inner: vec![],
+                                }
+                            }),
+                        }
+                    })
+                    .collect::<Result<Vec<Series>, ShellError>>()?;
+
+                let df_new = DataFrame::new(new_cols).map_err(|e| ShellError::GenericError {
+                    error: "Error appending dataframe".into(),
+                    msg: format!("Unable to append dataframes: {e}"),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?;
+
+                Ok(NuDataFrame::new(false, df_new))
+            }
+        }
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_expression/custom_value.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_expression/custom_value.rs
new file mode 100644
index 0000000000..8f5f478c8c
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_expression/custom_value.rs
@@ -0,0 +1,229 @@
+use crate::{
+    values::{CustomValueSupport, PolarsPluginCustomValue},
+    Cacheable, PolarsPlugin,
+};
+use std::ops::{Add, Div, Mul, Rem, Sub};
+
+use super::NuExpression;
+use nu_plugin::EngineInterface;
+use nu_protocol::{
+    ast::{Comparison, Math, Operator},
+    CustomValue, ShellError, Span, Type, Value,
+};
+use polars::prelude::Expr;
+use serde::{Deserialize, Serialize};
+use uuid::Uuid;
+
+const TYPE_NAME: &str = "NuExpression";
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct NuExpressionCustomValue {
+    pub id: Uuid,
+    #[serde(skip)]
+    pub expr: Option<NuExpression>,
+}
+
+// CustomValue implementation for NuDataFrame
+#[typetag::serde]
+impl CustomValue for NuExpressionCustomValue {
+    fn clone_value(&self, span: nu_protocol::Span) -> Value {
+        let cloned = self.clone();
+        Value::custom(Box::new(cloned), span)
+    }
+
+    fn type_name(&self) -> String {
+        TYPE_NAME.into()
+    }
+
+    fn to_base_value(&self, span: Span) -> Result<Value, ShellError> {
+        Ok(Value::string(
+            "NuExpressionCustomValue: custom_value_to_base_value should've been called",
+            span,
+        ))
+    }
+
+    fn as_mut_any(&mut self) -> &mut dyn std::any::Any {
+        self
+    }
+
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+
+    fn notify_plugin_on_drop(&self) -> bool {
+        true
+    }
+}
+
+fn compute_with_value(
+    (plugin, engine): (&PolarsPlugin, &EngineInterface),
+    left: &NuExpression,
+    lhs_span: Span,
+    operator: Operator,
+    op: Span,
+    right: &Value,
+) -> Result<Value, ShellError> {
+    let rhs_span = right.span();
+    match right {
+        Value::Custom { val: rhs, .. } => {
+            let rhs = rhs.as_any().downcast_ref::<NuExpression>().ok_or_else(|| {
+                ShellError::DowncastNotPossible {
+                    msg: "Unable to create expression".into(),
+                    span: rhs_span,
+                }
+            })?;
+
+            match rhs.as_ref() {
+                polars::prelude::Expr::Literal(..) => with_operator(
+                    (plugin, engine),
+                    operator,
+                    left,
+                    rhs,
+                    lhs_span,
+                    right.span(),
+                    op,
+                ),
+                _ => Err(ShellError::TypeMismatch {
+                    err_message: "Only literal expressions or number".into(),
+                    span: right.span(),
+                }),
+            }
+        }
+        _ => {
+            let rhs = NuExpression::try_from_value(plugin, right)?;
+            with_operator(
+                (plugin, engine),
+                operator,
+                left,
+                &rhs,
+                lhs_span,
+                right.span(),
+                op,
+            )
+        }
+    }
+}
+
+fn with_operator(
+    (plugin, engine): (&PolarsPlugin, &EngineInterface),
+    operator: Operator,
+    left: &NuExpression,
+    right: &NuExpression,
+    lhs_span: Span,
+    rhs_span: Span,
+    op_span: Span,
+) -> Result<Value, ShellError> {
+    match operator {
+        Operator::Math(Math::Plus) => {
+            apply_arithmetic(plugin, engine, left, right, lhs_span, Add::add)
+        }
+        Operator::Math(Math::Minus) => {
+            apply_arithmetic(plugin, engine, left, right, lhs_span, Sub::sub)
+        }
+        Operator::Math(Math::Multiply) => {
+            apply_arithmetic(plugin, engine, left, right, lhs_span, Mul::mul)
+        }
+        Operator::Math(Math::Divide) => {
+            apply_arithmetic(plugin, engine, left, right, lhs_span, Div::div)
+        }
+        Operator::Math(Math::Modulo) => {
+            apply_arithmetic(plugin, engine, left, right, lhs_span, Rem::rem)
+        }
+        Operator::Math(Math::FloorDivision) => {
+            apply_arithmetic(plugin, engine, left, right, lhs_span, Div::div)
+        }
+        Operator::Comparison(Comparison::Equal) => Ok(left
+            .clone()
+            .apply_with_expr(right.clone(), Expr::eq)
+            .cache(plugin, engine)?
+            .into_value(lhs_span)),
+        Operator::Comparison(Comparison::NotEqual) => Ok(left
+            .clone()
+            .apply_with_expr(right.clone(), Expr::neq)
+            .cache(plugin, engine)?
+            .into_value(lhs_span)),
+        Operator::Comparison(Comparison::GreaterThan) => Ok(left
+            .clone()
+            .apply_with_expr(right.clone(), Expr::gt)
+            .cache(plugin, engine)?
+            .into_value(lhs_span)),
+        Operator::Comparison(Comparison::GreaterThanOrEqual) => Ok(left
+            .clone()
+            .apply_with_expr(right.clone(), Expr::gt_eq)
+            .cache(plugin, engine)?
+            .into_value(lhs_span)),
+        Operator::Comparison(Comparison::LessThan) => Ok(left
+            .clone()
+            .apply_with_expr(right.clone(), Expr::lt)
+            .cache(plugin, engine)?
+            .into_value(lhs_span)),
+        Operator::Comparison(Comparison::LessThanOrEqual) => Ok(left
+            .clone()
+            .apply_with_expr(right.clone(), Expr::lt_eq)
+            .cache(plugin, engine)?
+            .into_value(lhs_span)),
+        _ => Err(ShellError::OperatorMismatch {
+            op_span,
+            lhs_ty: Type::Custom(TYPE_NAME.into()).to_string(),
+            lhs_span,
+            rhs_ty: Type::Custom(TYPE_NAME.into()).to_string(),
+            rhs_span,
+        }),
+    }
+}
+
+fn apply_arithmetic<F>(
+    plugin: &PolarsPlugin,
+    engine: &EngineInterface,
+    left: &NuExpression,
+    right: &NuExpression,
+    span: Span,
+    f: F,
+) -> Result<Value, ShellError>
+where
+    F: Fn(Expr, Expr) -> Expr,
+{
+    let expr: NuExpression = f(left.as_ref().clone(), right.as_ref().clone()).into();
+
+    Ok(expr.cache(plugin, engine)?.into_value(span))
+}
+
+impl PolarsPluginCustomValue for NuExpressionCustomValue {
+    type PolarsPluginObjectType = NuExpression;
+
+    fn custom_value_operation(
+        &self,
+        plugin: &crate::PolarsPlugin,
+        engine: &nu_plugin::EngineInterface,
+        lhs_span: Span,
+        operator: nu_protocol::Spanned<nu_protocol::ast::Operator>,
+        right: Value,
+    ) -> Result<Value, ShellError> {
+        let expr = NuExpression::try_from_custom_value(plugin, self)?;
+        compute_with_value(
+            (plugin, engine),
+            &expr,
+            lhs_span,
+            operator.item,
+            operator.span,
+            &right,
+        )
+    }
+
+    fn custom_value_to_base_value(
+        &self,
+        plugin: &crate::PolarsPlugin,
+        _engine: &nu_plugin::EngineInterface,
+    ) -> Result<Value, ShellError> {
+        let expr = NuExpression::try_from_custom_value(plugin, self)?;
+        expr.base_value(Span::unknown())
+    }
+
+    fn id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn internal(&self) -> &Option<Self::PolarsPluginObjectType> {
+        &self.expr
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_expression/mod.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_expression/mod.rs
new file mode 100644
index 0000000000..a6e26efc8d
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_expression/mod.rs
@@ -0,0 +1,495 @@
+mod custom_value;
+
+use nu_protocol::{record, ShellError, Span, Value};
+use polars::prelude::{col, AggExpr, Expr, Literal};
+use serde::{Deserialize, Deserializer, Serialize, Serializer};
+use uuid::Uuid;
+
+use crate::{Cacheable, PolarsPlugin};
+
+pub use self::custom_value::NuExpressionCustomValue;
+
+use super::{CustomValueSupport, PolarsPluginObject, PolarsPluginType};
+
+// Polars Expression wrapper for Nushell operations
+// Object is behind and Option to allow easy implementation of
+// the Deserialize trait
+#[derive(Default, Clone, Debug)]
+pub struct NuExpression {
+    pub id: Uuid,
+    expr: Option<Expr>,
+}
+
+// Mocked serialization of the LazyFrame object
+impl Serialize for NuExpression {
+    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+    where
+        S: Serializer,
+    {
+        serializer.serialize_none()
+    }
+}
+
+// Mocked deserialization of the LazyFrame object
+impl<'de> Deserialize<'de> for NuExpression {
+    fn deserialize<D>(_deserializer: D) -> Result<Self, D::Error>
+    where
+        D: Deserializer<'de>,
+    {
+        Ok(NuExpression::default())
+    }
+}
+
+// Referenced access to the real LazyFrame
+impl AsRef<Expr> for NuExpression {
+    fn as_ref(&self) -> &polars::prelude::Expr {
+        // The only case when there cannot be an expr is if it is created
+        // using the default function or if created by deserializing something
+        self.expr.as_ref().expect("there should always be a frame")
+    }
+}
+
+impl AsMut<Expr> for NuExpression {
+    fn as_mut(&mut self) -> &mut polars::prelude::Expr {
+        // The only case when there cannot be an expr is if it is created
+        // using the default function or if created by deserializing something
+        self.expr.as_mut().expect("there should always be a frame")
+    }
+}
+
+impl From<Expr> for NuExpression {
+    fn from(expr: Expr) -> Self {
+        Self::new(Some(expr))
+    }
+}
+
+impl NuExpression {
+    fn new(expr: Option<Expr>) -> Self {
+        Self {
+            id: Uuid::new_v4(),
+            expr,
+        }
+    }
+
+    pub fn to_polars(self) -> Expr {
+        self.expr.expect("Expression cannot be none to convert")
+    }
+
+    pub fn apply_with_expr<F>(self, other: NuExpression, f: F) -> Self
+    where
+        F: Fn(Expr, Expr) -> Expr,
+    {
+        let expr = self
+            .expr
+            .expect("Lazy expression must not be empty to apply");
+        let other = other
+            .expr
+            .expect("Lazy expression must not be empty to apply");
+
+        f(expr, other).into()
+    }
+
+    pub fn to_value(&self, span: Span) -> Result<Value, ShellError> {
+        expr_to_value(self.as_ref(), span)
+    }
+
+    // Convenient function to extract multiple Expr that could be inside a nushell Value
+    pub fn extract_exprs(plugin: &PolarsPlugin, value: Value) -> Result<Vec<Expr>, ShellError> {
+        ExtractedExpr::extract_exprs(plugin, value).map(ExtractedExpr::into_exprs)
+    }
+}
+
+#[derive(Debug)]
+// Enum to represent the parsing of the expressions from Value
+enum ExtractedExpr {
+    Single(Expr),
+    List(Vec<ExtractedExpr>),
+}
+
+impl ExtractedExpr {
+    fn into_exprs(self) -> Vec<Expr> {
+        match self {
+            Self::Single(expr) => vec![expr],
+            Self::List(expressions) => expressions
+                .into_iter()
+                .flat_map(ExtractedExpr::into_exprs)
+                .collect(),
+        }
+    }
+
+    fn extract_exprs(plugin: &PolarsPlugin, value: Value) -> Result<ExtractedExpr, ShellError> {
+        match value {
+            Value::String { val, .. } => Ok(ExtractedExpr::Single(col(val.as_str()))),
+            Value::Custom { .. } => NuExpression::try_from_value(plugin, &value)
+                .map(NuExpression::to_polars)
+                .map(ExtractedExpr::Single),
+            Value::List { vals, .. } => vals
+                .into_iter()
+                .map(|x| Self::extract_exprs(plugin, x))
+                .collect::<Result<Vec<ExtractedExpr>, ShellError>>()
+                .map(ExtractedExpr::List),
+            x => Err(ShellError::CantConvert {
+                to_type: "expression".into(),
+                from_type: x.get_type().to_string(),
+                span: x.span(),
+                help: None,
+            }),
+        }
+    }
+}
+
+pub fn expr_to_value(expr: &Expr, span: Span) -> Result<Value, ShellError> {
+    match expr {
+        Expr::Alias(expr, alias) => Ok(Value::record(
+            record! {
+                "expr" => expr_to_value(expr.as_ref(), span)?,
+                "alias" => Value::string(alias.as_ref(), span),
+            },
+            span,
+        )),
+        Expr::Column(name) => Ok(Value::record(
+            record! {
+                "expr" => Value::string("column", span),
+                "value" => Value::string(name.to_string(), span),
+            },
+            span,
+        )),
+        Expr::Columns(columns) => {
+            let value = columns.iter().map(|col| Value::string(col, span)).collect();
+            Ok(Value::record(
+                record! {
+                    "expr" => Value::string("columns", span),
+                    "value" => Value::list(value, span),
+                },
+                span,
+            ))
+        }
+        Expr::Literal(literal) => Ok(Value::record(
+            record! {
+                "expr" => Value::string("literal", span),
+                "value" => Value::string(format!("{literal:?}"), span),
+            },
+            span,
+        )),
+        Expr::BinaryExpr { left, op, right } => Ok(Value::record(
+            record! {
+                "left" => expr_to_value(left, span)?,
+                "op" => Value::string(format!("{op:?}"), span),
+                "right" => expr_to_value(right, span)?,
+            },
+            span,
+        )),
+        Expr::Ternary {
+            predicate,
+            truthy,
+            falsy,
+        } => Ok(Value::record(
+            record! {
+                "predicate" => expr_to_value(predicate.as_ref(), span)?,
+                "truthy" => expr_to_value(truthy.as_ref(), span)?,
+                "falsy" => expr_to_value(falsy.as_ref(), span)?,
+            },
+            span,
+        )),
+        Expr::Agg(agg_expr) => {
+            let value = match agg_expr {
+                AggExpr::Min { input: expr, .. }
+                | AggExpr::Max { input: expr, .. }
+                | AggExpr::Median(expr)
+                | AggExpr::NUnique(expr)
+                | AggExpr::First(expr)
+                | AggExpr::Last(expr)
+                | AggExpr::Mean(expr)
+                | AggExpr::Implode(expr)
+                | AggExpr::Count(expr, _)
+                | AggExpr::Sum(expr)
+                | AggExpr::AggGroups(expr)
+                | AggExpr::Std(expr, _)
+                | AggExpr::Var(expr, _) => expr_to_value(expr.as_ref(), span),
+                AggExpr::Quantile {
+                    expr,
+                    quantile,
+                    interpol,
+                } => Ok(Value::record(
+                    record! {
+                        "expr" => expr_to_value(expr.as_ref(), span)?,
+                        "quantile" => expr_to_value(quantile.as_ref(), span)?,
+                        "interpol" => Value::string(format!("{interpol:?}"), span),
+                    },
+                    span,
+                )),
+            };
+
+            Ok(Value::record(
+                record! {
+                    "expr" => Value::string("agg", span),
+                    "value" => value?,
+                },
+                span,
+            ))
+        }
+        Expr::Len => Ok(Value::record(
+            record! { "expr" => Value::string("count", span) },
+            span,
+        )),
+        Expr::Wildcard => Ok(Value::record(
+            record! { "expr" => Value::string("wildcard", span) },
+            span,
+        )),
+        Expr::Explode(expr) => Ok(Value::record(
+            record! { "expr" => expr_to_value(expr.as_ref(), span)? },
+            span,
+        )),
+        Expr::KeepName(expr) => Ok(Value::record(
+            record! { "expr" => expr_to_value(expr.as_ref(), span)? },
+            span,
+        )),
+        Expr::Nth(i) => Ok(Value::record(
+            record! { "expr" => Value::int(*i, span) },
+            span,
+        )),
+        Expr::DtypeColumn(dtypes) => {
+            let vals = dtypes
+                .iter()
+                .map(|d| Value::string(format!("{d}"), span))
+                .collect();
+
+            Ok(Value::list(vals, span))
+        }
+        Expr::Sort { expr, options } => Ok(Value::record(
+            record! {
+                "expr" => expr_to_value(expr.as_ref(), span)?,
+                "options" => Value::string(format!("{options:?}"), span),
+            },
+            span,
+        )),
+        Expr::Cast {
+            expr,
+            data_type,
+            strict,
+        } => Ok(Value::record(
+            record! {
+                "expr" => expr_to_value(expr.as_ref(), span)?,
+                "dtype" => Value::string(format!("{data_type:?}"), span),
+                "strict" => Value::bool(*strict, span),
+            },
+            span,
+        )),
+        Expr::Gather {
+            expr,
+            idx,
+            returns_scalar: _,
+        } => Ok(Value::record(
+            record! {
+                "expr" => expr_to_value(expr.as_ref(), span)?,
+                "idx" => expr_to_value(idx.as_ref(), span)?,
+            },
+            span,
+        )),
+        Expr::SortBy {
+            expr,
+            by,
+            descending,
+        } => {
+            let by: Result<Vec<Value>, ShellError> =
+                by.iter().map(|b| expr_to_value(b, span)).collect();
+            let descending: Vec<Value> = descending.iter().map(|r| Value::bool(*r, span)).collect();
+
+            Ok(Value::record(
+                record! {
+                    "expr" => expr_to_value(expr.as_ref(), span)?,
+                    "by" => Value::list(by?, span),
+                    "descending" => Value::list(descending, span),
+                },
+                span,
+            ))
+        }
+        Expr::Filter { input, by } => Ok(Value::record(
+            record! {
+                "input" => expr_to_value(input.as_ref(), span)?,
+                "by" => expr_to_value(by.as_ref(), span)?,
+            },
+            span,
+        )),
+        Expr::Slice {
+            input,
+            offset,
+            length,
+        } => Ok(Value::record(
+            record! {
+                "input" => expr_to_value(input.as_ref(), span)?,
+                "offset" => expr_to_value(offset.as_ref(), span)?,
+                "length" => expr_to_value(length.as_ref(), span)?,
+            },
+            span,
+        )),
+        Expr::Exclude(expr, excluded) => {
+            let excluded = excluded
+                .iter()
+                .map(|e| Value::string(format!("{e:?}"), span))
+                .collect();
+
+            Ok(Value::record(
+                record! {
+                    "expr" => expr_to_value(expr.as_ref(), span)?,
+                    "excluded" => Value::list(excluded, span),
+                },
+                span,
+            ))
+        }
+        Expr::RenameAlias { expr, function } => Ok(Value::record(
+            record! {
+                "expr" => expr_to_value(expr.as_ref(), span)?,
+                "function" => Value::string(format!("{function:?}"), span),
+            },
+            span,
+        )),
+        Expr::AnonymousFunction {
+            input,
+            function,
+            output_type,
+            options,
+        } => {
+            let input: Result<Vec<Value>, ShellError> =
+                input.iter().map(|e| expr_to_value(e, span)).collect();
+            Ok(Value::record(
+                record! {
+                    "input" => Value::list(input?, span),
+                    "function" => Value::string(format!("{function:?}"), span),
+                    "output_type" => Value::string(format!("{output_type:?}"), span),
+                    "options" => Value::string(format!("{options:?}"), span),
+                },
+                span,
+            ))
+        }
+        Expr::Function {
+            input,
+            function,
+            options,
+        } => {
+            let input: Result<Vec<Value>, ShellError> =
+                input.iter().map(|e| expr_to_value(e, span)).collect();
+            Ok(Value::record(
+                record! {
+                    "input" => Value::list(input?, span),
+                    "function" => Value::string(format!("{function:?}"), span),
+                    "options" => Value::string(format!("{options:?}"), span),
+                },
+                span,
+            ))
+        }
+        Expr::Window {
+            function,
+            partition_by,
+            options,
+        } => {
+            let partition_by: Result<Vec<Value>, ShellError> = partition_by
+                .iter()
+                .map(|e| expr_to_value(e, span))
+                .collect();
+
+            Ok(Value::record(
+                record! {
+                    "function" => expr_to_value(function, span)?,
+                    "partition_by" => Value::list(partition_by?, span),
+                    "options" => Value::string(format!("{options:?}"), span),
+                },
+                span,
+            ))
+        }
+        Expr::SubPlan(_, _) => Err(ShellError::UnsupportedInput {
+            msg: "Expressions of type SubPlan are not yet supported".to_string(),
+            input: format!("Expression is {expr:?}"),
+            msg_span: span,
+            input_span: Span::unknown(),
+        }),
+        // the parameter polars_plan::dsl::selector::Selector is not publicly exposed.
+        // I am not sure what we can meaningfully do with this at this time.
+        Expr::Selector(_) => Err(ShellError::UnsupportedInput {
+            msg: "Expressions of type Selector to Nu Values is not yet supported".to_string(),
+            input: format!("Expression is {expr:?}"),
+            msg_span: span,
+            input_span: Span::unknown(),
+        }),
+    }
+}
+
+impl Cacheable for NuExpression {
+    fn cache_id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn to_cache_value(&self) -> Result<PolarsPluginObject, ShellError> {
+        Ok(PolarsPluginObject::NuExpression(self.clone()))
+    }
+
+    fn from_cache_value(cv: PolarsPluginObject) -> Result<Self, ShellError> {
+        match cv {
+            PolarsPluginObject::NuExpression(df) => Ok(df),
+            _ => Err(ShellError::GenericError {
+                error: "Cache value is not an expression".into(),
+                msg: "".into(),
+                span: None,
+                help: None,
+                inner: vec![],
+            }),
+        }
+    }
+}
+
+impl CustomValueSupport for NuExpression {
+    type CV = NuExpressionCustomValue;
+
+    fn custom_value(self) -> Self::CV {
+        NuExpressionCustomValue {
+            id: self.id,
+            expr: Some(self),
+        }
+    }
+
+    fn get_type_static() -> PolarsPluginType {
+        PolarsPluginType::NuExpression
+    }
+
+    fn try_from_value(plugin: &PolarsPlugin, value: &Value) -> Result<Self, ShellError> {
+        match value {
+            Value::Custom { val, .. } => {
+                if let Some(cv) = val.as_any().downcast_ref::<Self::CV>() {
+                    Self::try_from_custom_value(plugin, cv)
+                } else {
+                    Err(ShellError::CantConvert {
+                        to_type: Self::get_type_static().to_string(),
+                        from_type: value.get_type().to_string(),
+                        span: value.span(),
+                        help: None,
+                    })
+                }
+            }
+            Value::String { val, .. } => Ok(val.to_owned().lit().into()),
+            Value::Int { val, .. } => Ok(val.to_owned().lit().into()),
+            Value::Bool { val, .. } => Ok(val.to_owned().lit().into()),
+            Value::Float { val, .. } => Ok(val.to_owned().lit().into()),
+            x => Err(ShellError::CantConvert {
+                to_type: "lazy expression".into(),
+                from_type: x.get_type().to_string(),
+                span: x.span(),
+                help: None,
+            }),
+        }
+    }
+
+    fn can_downcast(value: &Value) -> bool {
+        match value {
+            Value::Custom { val, .. } => val.as_any().downcast_ref::<Self::CV>().is_some(),
+            Value::List { vals, .. } => vals.iter().all(Self::can_downcast),
+            Value::String { .. } | Value::Int { .. } | Value::Bool { .. } | Value::Float { .. } => {
+                true
+            }
+            _ => false,
+        }
+    }
+
+    fn base_value(self, _span: Span) -> Result<Value, ShellError> {
+        self.to_value(Span::unknown())
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_lazyframe/custom_value.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_lazyframe/custom_value.rs
new file mode 100644
index 0000000000..731d210dd8
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_lazyframe/custom_value.rs
@@ -0,0 +1,86 @@
+use std::cmp::Ordering;
+
+use nu_plugin::EngineInterface;
+use nu_protocol::{CustomValue, ShellError, Span, Value};
+use serde::{Deserialize, Serialize};
+use uuid::Uuid;
+
+use crate::{
+    values::{CustomValueSupport, NuDataFrame, PolarsPluginCustomValue},
+    PolarsPlugin,
+};
+
+use super::NuLazyFrame;
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct NuLazyFrameCustomValue {
+    pub id: Uuid,
+    #[serde(skip)]
+    pub lazyframe: Option<NuLazyFrame>,
+}
+
+// CustomValue implementation for NuDataFrame
+#[typetag::serde]
+impl CustomValue for NuLazyFrameCustomValue {
+    fn clone_value(&self, span: nu_protocol::Span) -> Value {
+        Value::custom(Box::new(self.clone()), span)
+    }
+
+    fn type_name(&self) -> String {
+        "NuLazyFrameCustomValue".into()
+    }
+
+    fn to_base_value(&self, span: Span) -> Result<Value, ShellError> {
+        Ok(Value::string(
+            "NuLazyFrameCustomValue: custom_value_to_base_value should've been called",
+            span,
+        ))
+    }
+
+    fn as_mut_any(&mut self) -> &mut dyn std::any::Any {
+        self
+    }
+
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+
+    fn notify_plugin_on_drop(&self) -> bool {
+        true
+    }
+}
+
+impl PolarsPluginCustomValue for NuLazyFrameCustomValue {
+    type PolarsPluginObjectType = NuLazyFrame;
+
+    fn custom_value_to_base_value(
+        &self,
+        plugin: &crate::PolarsPlugin,
+        _engine: &nu_plugin::EngineInterface,
+    ) -> Result<Value, ShellError> {
+        let lazy = NuLazyFrame::try_from_custom_value(plugin, self)?;
+        lazy.base_value(Span::unknown())
+    }
+
+    fn id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn internal(&self) -> &Option<Self::PolarsPluginObjectType> {
+        &self.lazyframe
+    }
+
+    fn custom_value_partial_cmp(
+        &self,
+        plugin: &PolarsPlugin,
+        _engine: &EngineInterface,
+        other_value: Value,
+    ) -> Result<Option<Ordering>, ShellError> {
+        // to compare, we need to convert to NuDataframe
+        let df = NuLazyFrame::try_from_custom_value(plugin, self)?;
+        let df = df.collect(other_value.span())?;
+        let other = NuDataFrame::try_from_value_coerce(plugin, &other_value, other_value.span())?;
+        let res = df.is_equal(&other);
+        Ok(res)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_lazyframe/mod.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_lazyframe/mod.rs
new file mode 100644
index 0000000000..75f4791032
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_lazyframe/mod.rs
@@ -0,0 +1,169 @@
+mod custom_value;
+
+use crate::{Cacheable, PolarsPlugin};
+
+use super::{
+    cant_convert_err, CustomValueSupport, NuDataFrame, NuExpression, NuSchema, PolarsPluginObject,
+    PolarsPluginType,
+};
+use core::fmt;
+use nu_protocol::{record, PipelineData, ShellError, Span, Value};
+use polars::prelude::{Expr, IntoLazy, LazyFrame};
+use std::sync::Arc;
+use uuid::Uuid;
+
+pub use custom_value::NuLazyFrameCustomValue;
+
+// Lazyframe wrapper for Nushell operations
+// Polars LazyFrame is behind and Option to allow easy implementation of
+// the Deserialize trait
+#[derive(Default, Clone)]
+pub struct NuLazyFrame {
+    pub id: Uuid,
+    pub lazy: Arc<LazyFrame>,
+    pub from_eager: bool,
+}
+
+impl fmt::Debug for NuLazyFrame {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        write!(f, "NuLazyframe")
+    }
+}
+
+impl From<LazyFrame> for NuLazyFrame {
+    fn from(lazy_frame: LazyFrame) -> Self {
+        NuLazyFrame::new(false, lazy_frame)
+    }
+}
+
+impl NuLazyFrame {
+    pub fn new(from_eager: bool, lazy: LazyFrame) -> Self {
+        Self {
+            id: Uuid::new_v4(),
+            lazy: Arc::new(lazy),
+            from_eager,
+        }
+    }
+
+    pub fn from_dataframe(df: NuDataFrame) -> Self {
+        let lazy = df.as_ref().clone().lazy();
+        NuLazyFrame::new(true, lazy)
+    }
+
+    pub fn to_polars(&self) -> LazyFrame {
+        (*self.lazy).clone()
+    }
+
+    pub fn collect(self, span: Span) -> Result<NuDataFrame, ShellError> {
+        self.to_polars()
+            .collect()
+            .map_err(|e| ShellError::GenericError {
+                error: "Error collecting lazy frame".into(),
+                msg: e.to_string(),
+                span: Some(span),
+                help: None,
+                inner: vec![],
+            })
+            .map(|df| NuDataFrame::new(!self.from_eager, df))
+    }
+
+    pub fn apply_with_expr<F>(self, expr: NuExpression, f: F) -> Self
+    where
+        F: Fn(LazyFrame, Expr) -> LazyFrame,
+    {
+        let df = self.to_polars();
+        let expr = expr.to_polars();
+        let new_frame = f(df, expr);
+        Self::new(self.from_eager, new_frame)
+    }
+
+    pub fn schema(&self) -> Result<NuSchema, ShellError> {
+        let internal_schema = self.lazy.schema().map_err(|e| ShellError::GenericError {
+            error: "Error getting schema from lazy frame".into(),
+            msg: e.to_string(),
+            span: None,
+            help: None,
+            inner: vec![],
+        })?;
+        Ok(internal_schema.into())
+    }
+
+    /// Get a NuLazyFrame from the value. This differs from try_from_value as it will coerce a
+    /// NuDataFrame into a NuLazyFrame
+    pub fn try_from_value_coerce(
+        plugin: &PolarsPlugin,
+        value: &Value,
+    ) -> Result<NuLazyFrame, ShellError> {
+        match PolarsPluginObject::try_from_value(plugin, value)? {
+            PolarsPluginObject::NuDataFrame(df) => Ok(df.lazy()),
+            PolarsPluginObject::NuLazyFrame(lazy) => Ok(lazy),
+            _ => Err(cant_convert_err(
+                value,
+                &[PolarsPluginType::NuDataFrame, PolarsPluginType::NuLazyFrame],
+            )),
+        }
+    }
+
+    /// This differs from try_from_pipeline as it will attempt to coerce the type into a NuDataFrame.
+    /// So, if the pipeline type is a NuLazyFrame it will be collected and returned as NuDataFrame.
+    pub fn try_from_pipeline_coerce(
+        plugin: &PolarsPlugin,
+        input: PipelineData,
+        span: Span,
+    ) -> Result<Self, ShellError> {
+        let value = input.into_value(span);
+        Self::try_from_value_coerce(plugin, &value)
+    }
+}
+
+impl Cacheable for NuLazyFrame {
+    fn cache_id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn to_cache_value(&self) -> Result<PolarsPluginObject, ShellError> {
+        Ok(PolarsPluginObject::NuLazyFrame(self.clone()))
+    }
+
+    fn from_cache_value(cv: PolarsPluginObject) -> Result<Self, ShellError> {
+        match cv {
+            PolarsPluginObject::NuLazyFrame(df) => Ok(df),
+            _ => Err(ShellError::GenericError {
+                error: "Cache value is not a lazyframe".into(),
+                msg: "".into(),
+                span: None,
+                help: None,
+                inner: vec![],
+            }),
+        }
+    }
+}
+
+impl CustomValueSupport for NuLazyFrame {
+    type CV = NuLazyFrameCustomValue;
+
+    fn custom_value(self) -> Self::CV {
+        NuLazyFrameCustomValue {
+            id: self.id,
+            lazyframe: Some(self),
+        }
+    }
+
+    fn get_type_static() -> PolarsPluginType {
+        PolarsPluginType::NuLazyFrame
+    }
+
+    fn base_value(self, span: Span) -> Result<Value, ShellError> {
+        let optimized_plan = self
+            .lazy
+            .describe_optimized_plan()
+            .unwrap_or_else(|_| "<NOT AVAILABLE>".to_string());
+        Ok(Value::record(
+            record! {
+                "plan" => Value::string(self.lazy.describe_plan(), span),
+                "optimized_plan" => Value::string(optimized_plan, span),
+            },
+            span,
+        ))
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_lazygroupby/custom_value.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_lazygroupby/custom_value.rs
new file mode 100644
index 0000000000..03327259bb
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_lazygroupby/custom_value.rs
@@ -0,0 +1,63 @@
+use crate::values::{CustomValueSupport, PolarsPluginCustomValue};
+
+use super::NuLazyGroupBy;
+use nu_protocol::{CustomValue, ShellError, Span, Value};
+use serde::{Deserialize, Serialize};
+use uuid::Uuid;
+
+#[derive(Debug, Clone, Deserialize, Serialize)]
+pub struct NuLazyGroupByCustomValue {
+    pub id: Uuid,
+    #[serde(skip)]
+    pub groupby: Option<NuLazyGroupBy>,
+}
+
+#[typetag::serde]
+impl CustomValue for NuLazyGroupByCustomValue {
+    fn clone_value(&self, span: nu_protocol::Span) -> Value {
+        Value::custom(Box::new(self.clone()), span)
+    }
+
+    fn type_name(&self) -> String {
+        "NuLazyGroupByCustomValue".into()
+    }
+
+    fn to_base_value(&self, span: Span) -> Result<Value, ShellError> {
+        Ok(Value::string(
+            "NuLazyGroupByCustomValue: custom_value_to_base_value should've been called",
+            span,
+        ))
+    }
+
+    fn as_mut_any(&mut self) -> &mut dyn std::any::Any {
+        self
+    }
+
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+
+    fn notify_plugin_on_drop(&self) -> bool {
+        true
+    }
+}
+
+impl PolarsPluginCustomValue for NuLazyGroupByCustomValue {
+    type PolarsPluginObjectType = NuLazyGroupBy;
+
+    fn custom_value_to_base_value(
+        &self,
+        plugin: &crate::PolarsPlugin,
+        _engine: &nu_plugin::EngineInterface,
+    ) -> Result<Value, ShellError> {
+        NuLazyGroupBy::try_from_custom_value(plugin, self)?.base_value(Span::unknown())
+    }
+
+    fn id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn internal(&self) -> &Option<Self::PolarsPluginObjectType> {
+        &self.groupby
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_lazygroupby/mod.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_lazygroupby/mod.rs
new file mode 100644
index 0000000000..8540d13c6f
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_lazygroupby/mod.rs
@@ -0,0 +1,92 @@
+mod custom_value;
+
+use core::fmt;
+use nu_protocol::{record, ShellError, Span, Value};
+use polars::prelude::LazyGroupBy;
+use std::sync::Arc;
+use uuid::Uuid;
+
+use crate::Cacheable;
+
+pub use self::custom_value::NuLazyGroupByCustomValue;
+
+use super::{CustomValueSupport, NuSchema, PolarsPluginObject, PolarsPluginType};
+
+// Lazyframe wrapper for Nushell operations
+// Polars LazyFrame is behind and Option to allow easy implementation of
+// the Deserialize trait
+#[derive(Clone)]
+pub struct NuLazyGroupBy {
+    pub id: Uuid,
+    pub group_by: Arc<LazyGroupBy>,
+    pub schema: NuSchema,
+    pub from_eager: bool,
+}
+
+impl fmt::Debug for NuLazyGroupBy {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        write!(f, "NuLazyGroupBy")
+    }
+}
+
+impl NuLazyGroupBy {
+    pub fn new(group_by: LazyGroupBy, from_eager: bool, schema: NuSchema) -> Self {
+        NuLazyGroupBy {
+            id: Uuid::new_v4(),
+            group_by: Arc::new(group_by),
+            from_eager,
+            schema,
+        }
+    }
+
+    pub fn to_polars(&self) -> LazyGroupBy {
+        (*self.group_by).clone()
+    }
+}
+
+impl Cacheable for NuLazyGroupBy {
+    fn cache_id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn to_cache_value(&self) -> Result<PolarsPluginObject, ShellError> {
+        Ok(PolarsPluginObject::NuLazyGroupBy(self.clone()))
+    }
+
+    fn from_cache_value(cv: PolarsPluginObject) -> Result<Self, ShellError> {
+        match cv {
+            PolarsPluginObject::NuLazyGroupBy(df) => Ok(df),
+            _ => Err(ShellError::GenericError {
+                error: "Cache value is not a group by".into(),
+                msg: "".into(),
+                span: None,
+                help: None,
+                inner: vec![],
+            }),
+        }
+    }
+}
+
+impl CustomValueSupport for NuLazyGroupBy {
+    type CV = NuLazyGroupByCustomValue;
+
+    fn custom_value(self) -> Self::CV {
+        NuLazyGroupByCustomValue {
+            id: self.id,
+            groupby: Some(self),
+        }
+    }
+
+    fn get_type_static() -> PolarsPluginType {
+        PolarsPluginType::NuLazyGroupBy
+    }
+
+    fn base_value(self, _span: nu_protocol::Span) -> Result<nu_protocol::Value, ShellError> {
+        Ok(Value::record(
+            record! {
+                "LazyGroupBy" => Value::string("apply aggregation to complete execution plan", Span::unknown())
+            },
+            Span::unknown(),
+        ))
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_schema.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_schema.rs
new file mode 100644
index 0000000000..f684b8bb38
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_schema.rs
@@ -0,0 +1,383 @@
+use std::sync::Arc;
+
+use nu_protocol::{ShellError, Span, Value};
+use polars::prelude::{DataType, Field, Schema, SchemaRef, TimeUnit};
+
+#[derive(Debug, Clone)]
+pub struct NuSchema {
+    pub schema: SchemaRef,
+}
+
+impl NuSchema {
+    pub fn new(schema: Schema) -> Self {
+        Self {
+            schema: Arc::new(schema),
+        }
+    }
+}
+
+impl TryFrom<&Value> for NuSchema {
+    type Error = ShellError;
+    fn try_from(value: &Value) -> Result<Self, Self::Error> {
+        let schema = value_to_schema(value, Span::unknown())?;
+        Ok(Self::new(schema))
+    }
+}
+
+impl From<NuSchema> for Value {
+    fn from(schema: NuSchema) -> Self {
+        fields_to_value(schema.schema.iter_fields(), Span::unknown())
+    }
+}
+
+impl From<NuSchema> for SchemaRef {
+    fn from(val: NuSchema) -> Self {
+        Arc::clone(&val.schema)
+    }
+}
+
+impl From<SchemaRef> for NuSchema {
+    fn from(val: SchemaRef) -> Self {
+        Self { schema: val }
+    }
+}
+
+fn fields_to_value(fields: impl Iterator<Item = Field>, span: Span) -> Value {
+    let record = fields
+        .map(|field| {
+            let col = field.name().to_string();
+            let val = dtype_to_value(field.data_type(), span);
+            (col, val)
+        })
+        .collect();
+
+    Value::record(record, Span::unknown())
+}
+
+fn dtype_to_value(dtype: &DataType, span: Span) -> Value {
+    match dtype {
+        DataType::Struct(fields) => fields_to_value(fields.iter().cloned(), span),
+        _ => Value::string(dtype.to_string().replace('[', "<").replace(']', ">"), span),
+    }
+}
+
+fn value_to_schema(value: &Value, span: Span) -> Result<Schema, ShellError> {
+    let fields = value_to_fields(value, span)?;
+    let schema = Schema::from_iter(fields);
+    Ok(schema)
+}
+
+fn value_to_fields(value: &Value, span: Span) -> Result<Vec<Field>, ShellError> {
+    let fields = value
+        .as_record()?
+        .into_iter()
+        .map(|(col, val)| match val {
+            Value::Record { .. } => {
+                let fields = value_to_fields(val, span)?;
+                let dtype = DataType::Struct(fields);
+                Ok(Field::new(col, dtype))
+            }
+            _ => {
+                let dtype = str_to_dtype(&val.coerce_string()?, span)?;
+                Ok(Field::new(col, dtype))
+            }
+        })
+        .collect::<Result<Vec<Field>, ShellError>>()?;
+    Ok(fields)
+}
+
+pub fn str_to_dtype(dtype: &str, span: Span) -> Result<DataType, ShellError> {
+    match dtype {
+        "bool" => Ok(DataType::Boolean),
+        "u8" => Ok(DataType::UInt8),
+        "u16" => Ok(DataType::UInt16),
+        "u32" => Ok(DataType::UInt32),
+        "u64" => Ok(DataType::UInt64),
+        "i8" => Ok(DataType::Int8),
+        "i16" => Ok(DataType::Int16),
+        "i32" => Ok(DataType::Int32),
+        "i64" => Ok(DataType::Int64),
+        "f32" => Ok(DataType::Float32),
+        "f64" => Ok(DataType::Float64),
+        "str" => Ok(DataType::String),
+        "binary" => Ok(DataType::Binary),
+        "date" => Ok(DataType::Date),
+        "time" => Ok(DataType::Time),
+        "null" => Ok(DataType::Null),
+        "unknown" => Ok(DataType::Unknown),
+        "object" => Ok(DataType::Object("unknown", None)),
+        _ if dtype.starts_with("list") => {
+            let dtype = dtype
+                .trim_start_matches("list")
+                .trim_start_matches('<')
+                .trim_end_matches('>')
+                .trim();
+            let dtype = str_to_dtype(dtype, span)?;
+            Ok(DataType::List(Box::new(dtype)))
+        }
+        _ if dtype.starts_with("datetime") => {
+            let dtype = dtype
+                .trim_start_matches("datetime")
+                .trim_start_matches('<')
+                .trim_end_matches('>');
+            let mut split = dtype.split(',');
+            let next = split
+                .next()
+                .ok_or_else(|| ShellError::GenericError {
+                    error: "Invalid polars data type".into(),
+                    msg: "Missing time unit".into(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?
+                .trim();
+            let time_unit = str_to_time_unit(next, span)?;
+            let next = split
+                .next()
+                .ok_or_else(|| ShellError::GenericError {
+                    error: "Invalid polars data type".into(),
+                    msg: "Missing time zone".into(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?
+                .trim();
+            let timezone = if "*" == next {
+                None
+            } else {
+                Some(next.to_string())
+            };
+            Ok(DataType::Datetime(time_unit, timezone))
+        }
+        _ if dtype.starts_with("duration") => {
+            let inner = dtype.trim_start_matches("duration<").trim_end_matches('>');
+            let next = inner
+                .split(',')
+                .next()
+                .ok_or_else(|| ShellError::GenericError {
+                    error: "Invalid polars data type".into(),
+                    msg: "Missing time unit".into(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                })?
+                .trim();
+            let time_unit = str_to_time_unit(next, span)?;
+            Ok(DataType::Duration(time_unit))
+        }
+        _ => Err(ShellError::GenericError {
+            error: "Invalid polars data type".into(),
+            msg: format!("Unknown type: {dtype}"),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+fn str_to_time_unit(ts_string: &str, span: Span) -> Result<TimeUnit, ShellError> {
+    match ts_string {
+        "ms" => Ok(TimeUnit::Milliseconds),
+        "us" | "μs" => Ok(TimeUnit::Microseconds),
+        "ns" => Ok(TimeUnit::Nanoseconds),
+        _ => Err(ShellError::GenericError {
+            error: "Invalid polars data type".into(),
+            msg: "Invalid time unit".into(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        }),
+    }
+}
+
+#[cfg(test)]
+mod test {
+
+    use nu_protocol::record;
+
+    use super::*;
+
+    #[test]
+    fn test_value_to_schema() {
+        let address = record! {
+            "street" => Value::test_string("str"),
+            "city" => Value::test_string("str"),
+        };
+
+        let value = Value::test_record(record! {
+            "name" => Value::test_string("str"),
+            "age" => Value::test_string("i32"),
+            "address" => Value::test_record(address)
+        });
+
+        let schema = value_to_schema(&value, Span::unknown()).unwrap();
+        let expected = Schema::from_iter(vec![
+            Field::new("name", DataType::String),
+            Field::new("age", DataType::Int32),
+            Field::new(
+                "address",
+                DataType::Struct(vec![
+                    Field::new("street", DataType::String),
+                    Field::new("city", DataType::String),
+                ]),
+            ),
+        ]);
+        assert_eq!(schema, expected);
+    }
+
+    #[test]
+    fn test_dtype_str_to_schema_simple_types() {
+        let dtype = "bool";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Boolean;
+        assert_eq!(schema, expected);
+
+        let dtype = "u8";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::UInt8;
+        assert_eq!(schema, expected);
+
+        let dtype = "u16";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::UInt16;
+        assert_eq!(schema, expected);
+
+        let dtype = "u32";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::UInt32;
+        assert_eq!(schema, expected);
+
+        let dtype = "u64";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::UInt64;
+        assert_eq!(schema, expected);
+
+        let dtype = "i8";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Int8;
+        assert_eq!(schema, expected);
+
+        let dtype = "i16";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Int16;
+        assert_eq!(schema, expected);
+
+        let dtype = "i32";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Int32;
+        assert_eq!(schema, expected);
+
+        let dtype = "i64";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Int64;
+        assert_eq!(schema, expected);
+
+        let dtype = "str";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::String;
+        assert_eq!(schema, expected);
+
+        let dtype = "binary";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Binary;
+        assert_eq!(schema, expected);
+
+        let dtype = "date";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Date;
+        assert_eq!(schema, expected);
+
+        let dtype = "time";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Time;
+        assert_eq!(schema, expected);
+
+        let dtype = "null";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Null;
+        assert_eq!(schema, expected);
+
+        let dtype = "unknown";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Unknown;
+        assert_eq!(schema, expected);
+
+        let dtype = "object";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Object("unknown", None);
+        assert_eq!(schema, expected);
+    }
+
+    #[test]
+    fn test_dtype_str_schema_datetime() {
+        let dtype = "datetime<ms, *>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Datetime(TimeUnit::Milliseconds, None);
+        assert_eq!(schema, expected);
+
+        let dtype = "datetime<us, *>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Datetime(TimeUnit::Microseconds, None);
+        assert_eq!(schema, expected);
+
+        let dtype = "datetime<μs, *>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Datetime(TimeUnit::Microseconds, None);
+        assert_eq!(schema, expected);
+
+        let dtype = "datetime<ns, *>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Datetime(TimeUnit::Nanoseconds, None);
+        assert_eq!(schema, expected);
+
+        let dtype = "datetime<ms, UTC>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Datetime(TimeUnit::Milliseconds, Some("UTC".into()));
+        assert_eq!(schema, expected);
+
+        let dtype = "invalid";
+        let schema = str_to_dtype(dtype, Span::unknown());
+        assert!(schema.is_err())
+    }
+
+    #[test]
+    fn test_dtype_str_schema_duration() {
+        let dtype = "duration<ms>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Duration(TimeUnit::Milliseconds);
+        assert_eq!(schema, expected);
+
+        let dtype = "duration<us>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Duration(TimeUnit::Microseconds);
+        assert_eq!(schema, expected);
+
+        let dtype = "duration<μs>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Duration(TimeUnit::Microseconds);
+        assert_eq!(schema, expected);
+
+        let dtype = "duration<ns>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::Duration(TimeUnit::Nanoseconds);
+        assert_eq!(schema, expected);
+    }
+
+    #[test]
+    fn test_dtype_str_to_schema_list_types() {
+        let dtype = "list<i32>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::List(Box::new(DataType::Int32));
+        assert_eq!(schema, expected);
+
+        let dtype = "list<duration<ms>>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::List(Box::new(DataType::Duration(TimeUnit::Milliseconds)));
+        assert_eq!(schema, expected);
+
+        let dtype = "list<datetime<ms, *>>";
+        let schema = str_to_dtype(dtype, Span::unknown()).unwrap();
+        let expected = DataType::List(Box::new(DataType::Datetime(TimeUnit::Milliseconds, None)));
+        assert_eq!(schema, expected);
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_when/custom_value.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_when/custom_value.rs
new file mode 100644
index 0000000000..5d64bbf011
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_when/custom_value.rs
@@ -0,0 +1,65 @@
+use crate::values::{CustomValueSupport, PolarsPluginCustomValue};
+
+use super::NuWhen;
+use nu_protocol::{CustomValue, ShellError, Span, Value};
+use serde::{Deserialize, Serialize};
+use uuid::Uuid;
+
+#[derive(Debug, Clone, Deserialize, Serialize)]
+pub struct NuWhenCustomValue {
+    pub id: uuid::Uuid,
+    #[serde(skip)]
+    pub when: Option<NuWhen>,
+}
+
+// CustomValue implementation for NuWhen
+#[typetag::serde]
+impl CustomValue for NuWhenCustomValue {
+    fn clone_value(&self, span: nu_protocol::Span) -> Value {
+        Value::custom(Box::new(self.clone()), span)
+    }
+
+    fn type_name(&self) -> String {
+        "NuWhenCustomValue".into()
+    }
+
+    fn to_base_value(&self, span: Span) -> Result<Value, ShellError> {
+        Ok(Value::string(
+            "NuWhenCustomValue: custom_value_to_base_value should've been called",
+            span,
+        ))
+    }
+
+    fn as_mut_any(&mut self) -> &mut dyn std::any::Any {
+        self
+    }
+
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+
+    fn notify_plugin_on_drop(&self) -> bool {
+        true
+    }
+}
+
+impl PolarsPluginCustomValue for NuWhenCustomValue {
+    type PolarsPluginObjectType = NuWhen;
+
+    fn custom_value_to_base_value(
+        &self,
+        plugin: &crate::PolarsPlugin,
+        _engine: &nu_plugin::EngineInterface,
+    ) -> Result<Value, ShellError> {
+        let when = NuWhen::try_from_custom_value(plugin, self)?;
+        when.base_value(Span::unknown())
+    }
+
+    fn id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn internal(&self) -> &Option<Self::PolarsPluginObjectType> {
+        &self.when
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/nu_when/mod.rs b/crates/nu_plugin_polars/src/dataframe/values/nu_when/mod.rs
new file mode 100644
index 0000000000..89ee748454
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/nu_when/mod.rs
@@ -0,0 +1,128 @@
+mod custom_value;
+
+use core::fmt;
+use nu_protocol::{ShellError, Span, Value};
+use polars::prelude::{ChainedThen, Then};
+use serde::{Serialize, Serializer};
+use uuid::Uuid;
+
+use crate::Cacheable;
+
+pub use self::custom_value::NuWhenCustomValue;
+
+use super::{CustomValueSupport, PolarsPluginObject, PolarsPluginType};
+
+#[derive(Debug, Clone)]
+pub struct NuWhen {
+    pub id: Uuid,
+    pub when_type: NuWhenType,
+}
+
+#[derive(Clone)]
+pub enum NuWhenType {
+    Then(Box<Then>),
+    ChainedThen(ChainedThen),
+}
+
+// Mocked serialization of the LazyFrame object
+impl Serialize for NuWhen {
+    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+    where
+        S: Serializer,
+    {
+        serializer.serialize_none()
+    }
+}
+
+impl fmt::Debug for NuWhenType {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        write!(f, "NuWhen")
+    }
+}
+
+impl From<Then> for NuWhenType {
+    fn from(then: Then) -> Self {
+        NuWhenType::Then(Box::new(then))
+    }
+}
+
+impl From<ChainedThen> for NuWhenType {
+    fn from(chained_when: ChainedThen) -> Self {
+        NuWhenType::ChainedThen(chained_when)
+    }
+}
+
+impl From<NuWhenType> for NuWhen {
+    fn from(when_type: NuWhenType) -> Self {
+        Self::new(when_type)
+    }
+}
+
+impl From<Then> for NuWhen {
+    fn from(then: Then) -> Self {
+        Self::new(then.into())
+    }
+}
+
+impl From<ChainedThen> for NuWhen {
+    fn from(chained_then: ChainedThen) -> Self {
+        Self::new(chained_then.into())
+    }
+}
+
+impl NuWhen {
+    pub fn new(when_type: NuWhenType) -> Self {
+        Self {
+            id: Uuid::new_v4(),
+            when_type,
+        }
+    }
+}
+
+impl Cacheable for NuWhen {
+    fn cache_id(&self) -> &Uuid {
+        &self.id
+    }
+
+    fn to_cache_value(&self) -> Result<PolarsPluginObject, ShellError> {
+        Ok(PolarsPluginObject::NuWhen(self.clone()))
+    }
+
+    fn from_cache_value(cv: PolarsPluginObject) -> Result<Self, ShellError> {
+        match cv {
+            PolarsPluginObject::NuWhen(when) => Ok(when),
+            _ => Err(ShellError::GenericError {
+                error: "Cache value is not a dataframe".into(),
+                msg: "".into(),
+                span: None,
+                help: None,
+                inner: vec![],
+            }),
+        }
+    }
+}
+
+impl CustomValueSupport for NuWhen {
+    type CV = NuWhenCustomValue;
+
+    fn custom_value(self) -> Self::CV {
+        NuWhenCustomValue {
+            id: self.id,
+            when: Some(self),
+        }
+    }
+
+    fn get_type_static() -> PolarsPluginType {
+        PolarsPluginType::NuWhen
+    }
+
+    fn base_value(self, _span: nu_protocol::Span) -> Result<nu_protocol::Value, ShellError> {
+        let val: String = match self.when_type {
+            NuWhenType::Then(_) => "whenthen".into(),
+            NuWhenType::ChainedThen(_) => "whenthenthen".into(),
+        };
+
+        let value = Value::string(val, Span::unknown());
+        Ok(value)
+    }
+}
diff --git a/crates/nu_plugin_polars/src/dataframe/values/utils.rs b/crates/nu_plugin_polars/src/dataframe/values/utils.rs
new file mode 100644
index 0000000000..17e641cadc
--- /dev/null
+++ b/crates/nu_plugin_polars/src/dataframe/values/utils.rs
@@ -0,0 +1,90 @@
+use nu_protocol::{span as span_join, ShellError, Span, Spanned, Value};
+
+// Default value used when selecting rows from dataframe
+pub const DEFAULT_ROWS: usize = 5;
+
+// Converts a Vec<Value> to a Vec<Spanned<String>> with a Span marking the whole
+// location of the columns for error referencing
+// todo - fix
+#[allow(dead_code)]
+pub(crate) fn convert_columns(
+    columns: Vec<Value>,
+    span: Span,
+) -> Result<(Vec<Spanned<String>>, Span), ShellError> {
+    // First column span
+    let mut col_span = columns
+        .first()
+        .ok_or_else(|| ShellError::GenericError {
+            error: "Empty column list".into(),
+            msg: "Empty list found for command".into(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        })
+        .map(|v| v.span())?;
+
+    let res = columns
+        .into_iter()
+        .map(|value| {
+            let span = value.span();
+            match value {
+                Value::String { val, .. } => {
+                    col_span = span_join(&[col_span, span]);
+                    Ok(Spanned { item: val, span })
+                }
+                _ => Err(ShellError::GenericError {
+                    error: "Incorrect column format".into(),
+                    msg: "Only string as column name".into(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        })
+        .collect::<Result<Vec<Spanned<String>>, _>>()?;
+
+    Ok((res, col_span))
+}
+
+// Converts a Vec<Value> to a Vec<String> with a Span marking the whole
+// location of the columns for error referencing
+// todo - fix
+#[allow(dead_code)]
+pub(crate) fn convert_columns_string(
+    columns: Vec<Value>,
+    span: Span,
+) -> Result<(Vec<String>, Span), ShellError> {
+    // First column span
+    let mut col_span = columns
+        .first()
+        .ok_or_else(|| ShellError::GenericError {
+            error: "Empty column list".into(),
+            msg: "Empty list found for command".into(),
+            span: Some(span),
+            help: None,
+            inner: vec![],
+        })
+        .map(|v| v.span())?;
+
+    let res = columns
+        .into_iter()
+        .map(|value| {
+            let span = value.span();
+            match value {
+                Value::String { val, .. } => {
+                    col_span = span_join(&[col_span, span]);
+                    Ok(val)
+                }
+                _ => Err(ShellError::GenericError {
+                    error: "Incorrect column format".into(),
+                    msg: "Only string as column name".into(),
+                    span: Some(span),
+                    help: None,
+                    inner: vec![],
+                }),
+            }
+        })
+        .collect::<Result<Vec<String>, _>>()?;
+
+    Ok((res, col_span))
+}
diff --git a/crates/nu_plugin_polars/src/lib.rs b/crates/nu_plugin_polars/src/lib.rs
new file mode 100644
index 0000000000..3b8679b606
--- /dev/null
+++ b/crates/nu_plugin_polars/src/lib.rs
@@ -0,0 +1,207 @@
+use std::cmp::Ordering;
+
+pub use cache::{Cache, Cacheable};
+use dataframe::{stub::PolarsCmd, values::CustomValueType};
+use nu_plugin::{EngineInterface, Plugin, PluginCommand};
+
+mod cache;
+pub mod dataframe;
+pub use dataframe::*;
+use nu_protocol::{ast::Operator, CustomValue, LabeledError, Spanned, Value};
+
+use crate::{
+    eager::eager_commands, expressions::expr_commands, lazy::lazy_commands,
+    series::series_commands, values::PolarsPluginCustomValue,
+};
+
+#[macro_export]
+macro_rules! plugin_debug {
+    ($($arg:tt)*) => {{
+        if std::env::var("POLARS_PLUGIN_DEBUG")
+            .ok()
+            .filter(|x| x == "1" || x == "true")
+            .is_some() {
+            eprintln!($($arg)*);
+        }
+    }};
+}
+
+#[derive(Default)]
+pub struct PolarsPlugin {
+    pub(crate) cache: Cache,
+    /// For testing purposes only
+    pub(crate) disable_cache_drop: bool,
+}
+
+impl Plugin for PolarsPlugin {
+    fn commands(&self) -> Vec<Box<dyn PluginCommand<Plugin = Self>>> {
+        let mut commands: Vec<Box<dyn PluginCommand<Plugin = Self>>> = vec![Box::new(PolarsCmd)];
+        commands.append(&mut eager_commands());
+        commands.append(&mut lazy_commands());
+        commands.append(&mut expr_commands());
+        commands.append(&mut series_commands());
+        commands
+    }
+
+    fn custom_value_dropped(
+        &self,
+        engine: &EngineInterface,
+        custom_value: Box<dyn CustomValue>,
+    ) -> Result<(), LabeledError> {
+        if !self.disable_cache_drop {
+            let id = CustomValueType::try_from_custom_value(custom_value)?.id();
+            let _ = self.cache.remove(Some(engine), &id);
+        }
+        Ok(())
+    }
+
+    fn custom_value_to_base_value(
+        &self,
+        engine: &EngineInterface,
+        custom_value: Spanned<Box<dyn CustomValue>>,
+    ) -> Result<Value, LabeledError> {
+        let result = match CustomValueType::try_from_custom_value(custom_value.item)? {
+            CustomValueType::NuDataFrame(cv) => cv.custom_value_to_base_value(self, engine),
+            CustomValueType::NuLazyFrame(cv) => cv.custom_value_to_base_value(self, engine),
+            CustomValueType::NuExpression(cv) => cv.custom_value_to_base_value(self, engine),
+            CustomValueType::NuLazyGroupBy(cv) => cv.custom_value_to_base_value(self, engine),
+            CustomValueType::NuWhen(cv) => cv.custom_value_to_base_value(self, engine),
+        };
+        Ok(result?)
+    }
+
+    fn custom_value_operation(
+        &self,
+        engine: &EngineInterface,
+        left: Spanned<Box<dyn CustomValue>>,
+        operator: Spanned<Operator>,
+        right: Value,
+    ) -> Result<Value, LabeledError> {
+        let result = match CustomValueType::try_from_custom_value(left.item)? {
+            CustomValueType::NuDataFrame(cv) => {
+                cv.custom_value_operation(self, engine, left.span, operator, right)
+            }
+            CustomValueType::NuLazyFrame(cv) => {
+                cv.custom_value_operation(self, engine, left.span, operator, right)
+            }
+            CustomValueType::NuExpression(cv) => {
+                cv.custom_value_operation(self, engine, left.span, operator, right)
+            }
+            CustomValueType::NuLazyGroupBy(cv) => {
+                cv.custom_value_operation(self, engine, left.span, operator, right)
+            }
+            CustomValueType::NuWhen(cv) => {
+                cv.custom_value_operation(self, engine, left.span, operator, right)
+            }
+        };
+        Ok(result?)
+    }
+
+    fn custom_value_follow_path_int(
+        &self,
+        engine: &EngineInterface,
+        custom_value: Spanned<Box<dyn CustomValue>>,
+        index: Spanned<usize>,
+    ) -> Result<Value, LabeledError> {
+        let result = match CustomValueType::try_from_custom_value(custom_value.item)? {
+            CustomValueType::NuDataFrame(cv) => {
+                cv.custom_value_follow_path_int(self, engine, custom_value.span, index)
+            }
+            CustomValueType::NuLazyFrame(cv) => {
+                cv.custom_value_follow_path_int(self, engine, custom_value.span, index)
+            }
+            CustomValueType::NuExpression(cv) => {
+                cv.custom_value_follow_path_int(self, engine, custom_value.span, index)
+            }
+            CustomValueType::NuLazyGroupBy(cv) => {
+                cv.custom_value_follow_path_int(self, engine, custom_value.span, index)
+            }
+            CustomValueType::NuWhen(cv) => {
+                cv.custom_value_follow_path_int(self, engine, custom_value.span, index)
+            }
+        };
+        Ok(result?)
+    }
+
+    fn custom_value_follow_path_string(
+        &self,
+        engine: &EngineInterface,
+        custom_value: Spanned<Box<dyn CustomValue>>,
+        column_name: Spanned<String>,
+    ) -> Result<Value, LabeledError> {
+        let result = match CustomValueType::try_from_custom_value(custom_value.item)? {
+            CustomValueType::NuDataFrame(cv) => {
+                cv.custom_value_follow_path_string(self, engine, custom_value.span, column_name)
+            }
+            CustomValueType::NuLazyFrame(cv) => {
+                cv.custom_value_follow_path_string(self, engine, custom_value.span, column_name)
+            }
+            CustomValueType::NuExpression(cv) => {
+                cv.custom_value_follow_path_string(self, engine, custom_value.span, column_name)
+            }
+            CustomValueType::NuLazyGroupBy(cv) => {
+                cv.custom_value_follow_path_string(self, engine, custom_value.span, column_name)
+            }
+            CustomValueType::NuWhen(cv) => {
+                cv.custom_value_follow_path_string(self, engine, custom_value.span, column_name)
+            }
+        };
+        Ok(result?)
+    }
+
+    fn custom_value_partial_cmp(
+        &self,
+        engine: &EngineInterface,
+        custom_value: Box<dyn CustomValue>,
+        other_value: Value,
+    ) -> Result<Option<Ordering>, LabeledError> {
+        let result = match CustomValueType::try_from_custom_value(custom_value)? {
+            CustomValueType::NuDataFrame(cv) => {
+                cv.custom_value_partial_cmp(self, engine, other_value)
+            }
+            CustomValueType::NuLazyFrame(cv) => {
+                cv.custom_value_partial_cmp(self, engine, other_value)
+            }
+            CustomValueType::NuExpression(cv) => {
+                cv.custom_value_partial_cmp(self, engine, other_value)
+            }
+            CustomValueType::NuLazyGroupBy(cv) => {
+                cv.custom_value_partial_cmp(self, engine, other_value)
+            }
+            CustomValueType::NuWhen(cv) => cv.custom_value_partial_cmp(self, engine, other_value),
+        };
+        Ok(result?)
+    }
+}
+
+#[cfg(test)]
+pub mod test {
+    use super::*;
+    use crate::values::PolarsPluginObject;
+    use nu_command::IntoDatetime;
+    use nu_plugin_test_support::PluginTest;
+    use nu_protocol::ShellError;
+
+    pub fn test_polars_plugin_command(command: &impl PluginCommand) -> Result<(), ShellError> {
+        let mut plugin = PolarsPlugin::default();
+        plugin.disable_cache_drop = true;
+        let examples = command.examples();
+
+        // we need to cache values in the examples
+        for example in &examples {
+            if let Some(ref result) = example.result {
+                // if it's a polars plugin object, try to cache it
+                if let Ok(obj) = PolarsPluginObject::try_from_value(&plugin, result) {
+                    let id = obj.id();
+                    plugin.cache.insert(None, id, obj).unwrap();
+                }
+            }
+        }
+
+        PluginTest::new("polars", plugin.into())?
+            .add_decl(Box::new(IntoDatetime))?
+            .test_examples(&examples)?;
+
+        Ok(())
+    }
+}
diff --git a/crates/nu_plugin_polars/src/main.rs b/crates/nu_plugin_polars/src/main.rs
new file mode 100644
index 0000000000..e060d7cd6d
--- /dev/null
+++ b/crates/nu_plugin_polars/src/main.rs
@@ -0,0 +1,6 @@
+use nu_plugin::{serve_plugin, MsgPackSerializer};
+use nu_plugin_polars::PolarsPlugin;
+
+fn main() {
+    serve_plugin(&PolarsPlugin::default(), MsgPackSerializer {})
+}