Move dataframes support to a plugin (#12220)

WIP

This PR covers migration crates/nu-cmd-dataframes to a new plugin
./crates/nu_plugin_polars

## TODO List

Other:
- [X] Fix examples
- [x] Fix Plugin Test Harness
- [X] Move Cache to Mutex<BTreeMap>
- [X] Logic for disabling/enabling plugin GC based off whether items are
cached.
- [x] NuExpression custom values
- [X] Optimize caching (don't cache every object creation). 
- [x] Fix dataframe operations (in NuDataFrameCustomValue::operations)
- [x] Added plugin_debug! macro that for checking an env variable
POLARS_PLUGIN_DEBUG

Fix duplicated commands:
- [x] There are two polars median commands, one for lazy and one for
expr.. there should only be one that works for both. I temporarily
called on polars expr-median (inside expressions_macros.rs)
- [x] polars quantile (lazy, and expr). the expr one is temporarily
expr-median
- [x] polars is-in (renamed one series-is-in)

Commands:
- [x] AppendDF
- [x] CastDF
- [X] ColumnsDF
- [x] DataTypes
- [x] Summary
- [x] DropDF
- [x] DropDuplicates
- [x] DropNulls
- [x] Dummies
- [x] FilterWith
- [X] FirstDF
- [x] GetDF
- [x] LastDF
- [X] ListDF
- [x] MeltDF
- [X] OpenDataFrame
- [x] QueryDf
- [x] RenameDF
- [x] SampleDF
- [x] SchemaDF
- [x] ShapeDF
- [x] SliceDF
- [x] TakeDF
- [X] ToArrow
- [x] ToAvro
- [X] ToCSV
- [X] ToDataFrame
- [X] ToNu
- [x] ToParquet
- [x] ToJsonLines
- [x] WithColumn
- [x] ExprAlias
- [x] ExprArgWhere
- [x] ExprCol
- [x] ExprConcatStr
- [x] ExprCount
- [x] ExprLit
- [x] ExprWhen
- [x] ExprOtherwise
- [x] ExprQuantile
- [x] ExprList
- [x] ExprAggGroups
- [x] ExprCount
- [x] ExprIsIn
- [x] ExprNot
- [x] ExprMax
- [x] ExprMin
- [x] ExprSum
- [x] ExprMean
- [x] ExprMedian
- [x] ExprStd
- [x] ExprVar
- [x] ExprDatePart
- [X] LazyAggregate
- [x] LazyCache
- [X] LazyCollect
- [x] LazyFetch
- [x] LazyFillNA
- [x] LazyFillNull
- [x] LazyFilter
- [x] LazyJoin
- [x] LazyQuantile
- [x] LazyMedian
- [x] LazyReverse
- [x] LazySelect
- [x] LazySortBy
- [x] ToLazyFrame
- [x] ToLazyGroupBy
- [x] LazyExplode
- [x] LazyFlatten
- [x] AllFalse
- [x] AllTrue
- [x] ArgMax
- [x] ArgMin
- [x] ArgSort
- [x] ArgTrue
- [x] ArgUnique
- [x] AsDate
- [x] AsDateTime
- [x] Concatenate
- [x] Contains
- [x] Cumulative
- [x] GetDay
- [x] GetHour
- [x] GetMinute
- [x] GetMonth
- [x] GetNanosecond
- [x] GetOrdinal
- [x] GetSecond
- [x] GetWeek
- [x] GetWeekDay
- [x] GetYear
- [x] IsDuplicated
- [x] IsIn
- [x] IsNotNull
- [x] IsNull
- [x] IsUnique
- [x] NNull
- [x] NUnique
- [x] NotSeries
- [x] Replace
- [x] ReplaceAll
- [x] Rolling
- [x] SetSeries
- [x] SetWithIndex
- [x] Shift
- [x] StrLengths
- [x] StrSlice
- [x] StrFTime
- [x] ToLowerCase
- [x] ToUpperCase
- [x] Unique
- [x] ValueCount

---------

Co-authored-by: Jack Wright <jack.wright@disqo.com>

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)

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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())
+    }
+}

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)
+    }
+}

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),
+    ]
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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(),
+                    ))
+                }
+            })
+        }
+    }
+}

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(),
+                ))
+            }
+        },
+    )
+}

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)
+    }
+}

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)
+    }
+}

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,
+    ))
+}

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,
+    ))
+}

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,
+    ))
+}

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)
+    }
+}

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,
+    ))
+}

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)
+    }
+}

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,
+    ))
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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
+);

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)
+    }
+}

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)
+    }
+}

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),
+    ]
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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
+);

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)
+    }
+}

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),
+    ]
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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,
+        ))
+    }
+}

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![],
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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;

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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;

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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;

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)
+    }
+}

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)
+    }
+}

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),
+    ]
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}

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)
+    }
+}