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Series arithmetic (#3602)

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* operations with series

* contains operations with series

* Checked division and masked operations
This commit is contained in:
Fernando Herrera 2021-06-10 22:39:51 +01:00 committed by GitHub
parent 1d7c909080
commit c4163c3621
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13 changed files with 812 additions and 90 deletions
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25
Cargo.lock generated
View File

@ -207,7 +207,7 @@ checksum = "23b62fc65de8e4e7f52534fb52b0f3ed04746ae267519eef2a83941e8085068b"
[[package]]
name = "arrow"
version = "5.0.0-SNAPSHOT"
source = "git+https://github.com/apache/arrow-rs?rev=f26ffb3091ae355d246edc4a6fcc2c8e5b9bc570#f26ffb3091ae355d246edc4a6fcc2c8e5b9bc570"
source = "git+https://github.com/apache/arrow-rs?rev=0f55b828883b3b3afda43ae404b130d374e6f1a1#0f55b828883b3b3afda43ae404b130d374e6f1a1"
dependencies = [
"chrono",
"csv",
@ -3504,6 +3504,7 @@ dependencies = [
"num-bigint 0.3.2",
"num-format",
"num-traits 0.2.14",
"polars",
"query_interface",
"serde 1.0.126",
"sha2 0.9.5",
@ -4362,7 +4363,7 @@ dependencies = [
[[package]]
name = "parquet"
version = "5.0.0-SNAPSHOT"
source = "git+https://github.com/apache/arrow-rs?rev=f26ffb3091ae355d246edc4a6fcc2c8e5b9bc570#f26ffb3091ae355d246edc4a6fcc2c8e5b9bc570"
source = "git+https://github.com/apache/arrow-rs?rev=0f55b828883b3b3afda43ae404b130d374e6f1a1#0f55b828883b3b3afda43ae404b130d374e6f1a1"
dependencies = [
"arrow",
"base64 0.13.0",
@ -4600,8 +4601,8 @@ dependencies = [
[[package]]
name = "polars"
version = "0.14.0"
source = "git+https://github.com/pola-rs/polars?rev=a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd#a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd"
version = "0.14.1"
source = "git+https://github.com/pola-rs/polars?rev=9e1506cca9fb646fc55f949ab6345290c3d198a7#9e1506cca9fb646fc55f949ab6345290c3d198a7"
dependencies = [
"polars-core",
"polars-io",
@ -4610,8 +4611,8 @@ dependencies = [
[[package]]
name = "polars-arrow"
version = "0.14.0"
source = "git+https://github.com/pola-rs/polars?rev=a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd#a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd"
version = "0.14.1"
source = "git+https://github.com/pola-rs/polars?rev=9e1506cca9fb646fc55f949ab6345290c3d198a7#9e1506cca9fb646fc55f949ab6345290c3d198a7"
dependencies = [
"arrow",
"num 0.4.0",
@ -4620,8 +4621,8 @@ dependencies = [
[[package]]
name = "polars-core"
version = "0.14.0"
source = "git+https://github.com/pola-rs/polars?rev=a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd#a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd"
version = "0.14.1"
source = "git+https://github.com/pola-rs/polars?rev=9e1506cca9fb646fc55f949ab6345290c3d198a7#9e1506cca9fb646fc55f949ab6345290c3d198a7"
dependencies = [
"ahash",
"anyhow",
@ -4646,8 +4647,8 @@ dependencies = [
[[package]]
name = "polars-io"
version = "0.14.0"
source = "git+https://github.com/pola-rs/polars?rev=a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd#a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd"
version = "0.14.1"
source = "git+https://github.com/pola-rs/polars?rev=9e1506cca9fb646fc55f949ab6345290c3d198a7#9e1506cca9fb646fc55f949ab6345290c3d198a7"
dependencies = [
"ahash",
"anyhow",
@ -4669,8 +4670,8 @@ dependencies = [
[[package]]
name = "polars-lazy"
version = "0.14.0"
source = "git+https://github.com/pola-rs/polars?rev=a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd#a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd"
version = "0.14.1"
source = "git+https://github.com/pola-rs/polars?rev=9e1506cca9fb646fc55f949ab6345290c3d198a7#9e1506cca9fb646fc55f949ab6345290c3d198a7"
dependencies = [
"ahash",
"itertools",

1
Cargo.toml
View File

@ -156,6 +156,7 @@ table-pager = ["nu-command/table-pager"]
#dataframe feature for nushell
dataframe = [
"nu-engine/dataframe",
"nu-protocol/dataframe",
"nu-command/dataframe",
"nu-value-ext/dataframe",

6
crates/nu-command/Cargo.toml
View File

@ -101,10 +101,10 @@ zip = { version = "0.5.9", optional = true }
[dependencies.polars]
git = "https://github.com/pola-rs/polars"
rev = "a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd"
version = "0.14.0"
rev = "9e1506cca9fb646fc55f949ab6345290c3d198a7"
version = "0.14.1"
optional = true
features = ["parquet", "json", "random", "pivot"]
features = ["parquet", "json", "random", "pivot", "strings"]
[target.'cfg(unix)'.dependencies]
umask = "1.0.0"

6
crates/nu-command/src/commands/dataframe/groupby.rs
View File

@ -12,7 +12,7 @@ pub struct DataFrame;
impl WholeStreamCommand for DataFrame {
fn name(&self) -> &str {
"pls groupby"
"pls group-by"
}
fn usage(&self) -> &str {
@ -20,7 +20,7 @@ impl WholeStreamCommand for DataFrame {
}
fn signature(&self) -> Signature {
Signature::build("pls groupby").required(
Signature::build("pls group-by").required(
"by columns",
SyntaxShape::Table,
"groupby columns",
@ -34,7 +34,7 @@ impl WholeStreamCommand for DataFrame {
fn examples(&self) -> Vec<Example> {
vec![Example {
description: "Grouping by column a",
example: "[[a b]; [one 1] [one 2]] | pls to-df | pls groupby [a]",
example: "[[a b]; [one 1] [one 2]] | pls to-df | pls group-by [a]",
result: None,
}]
}

60
crates/nu-command/src/commands/dataframe/where_.rs
View File

@ -4,11 +4,11 @@ use nu_errors::ShellError;
use nu_protocol::{
dataframe::NuDataFrame,
hir::{CapturedBlock, ClassifiedCommand, Expression, Literal, Operator, SpannedExpression},
Primitive, Signature, SyntaxShape, UnspannedPathMember, UntaggedValue,
Primitive, Signature, SyntaxShape, UnspannedPathMember, UntaggedValue, Value,
};
use super::utils::parse_polars_error;
use polars::prelude::{ChunkCompare, Series};
use polars::prelude::{ChunkCompare, DataType, Series};
pub struct DataFrame;
@ -91,22 +91,8 @@ fn command(args: CommandArgs) -> Result<OutputStream, ShellError> {
}?;
let rhs = evaluate_baseline_expr(&expression.right, &args.args.context)?;
let right_condition = match &rhs.value {
UntaggedValue::Primitive(primitive) => Ok(primitive),
_ => Err(ShellError::labeled_error(
"Incorrect argument",
"Expected primitive values",
&rhs.tag.span,
)),
}?;
filter_dataframe(
args,
&col_name,
&col_name_span,
&right_condition,
&expression.op,
)
filter_dataframe(args, &col_name, &col_name_span, &rhs, &expression.op)
}
macro_rules! comparison_arm {
@ -145,16 +131,25 @@ fn filter_dataframe(
mut args: EvaluatedCommandArgs,
col_name: &str,
col_name_span: &Span,
right_condition: &Primitive,
rhs: &Value,
operator: &SpannedExpression,
) -> Result<OutputStream, ShellError> {
let right_condition = match &rhs.value {
UntaggedValue::Primitive(primitive) => Ok(primitive),
_ => Err(ShellError::labeled_error(
"Incorrect argument",
"Expected primitive values",
&rhs.tag.span,
)),
}?;
let span = args.call_info.name_tag.span;
let df = NuDataFrame::try_from_stream(&mut args.input, &span)?;
let col = df
.as_ref()
.column(col_name)
.map_err(|e| parse_polars_error::<&str>(&e, &col_name_span, None))?;
.map_err(|e| parse_polars_error::<&str>(&e, col_name_span, None))?;
let op = match &operator.expr {
Expression::Literal(Literal::Operator(op)) => Ok(op),
@ -176,6 +171,33 @@ fn filter_dataframe(
Operator::GreaterThanOrEqual => {
comparison_arm!(Series::gt_eq, col, right_condition, operator.span)
}
Operator::Contains => match col.dtype() {
DataType::Utf8 => match right_condition {
Primitive::String(pat) => {
let casted = col.utf8().map_err(|e| {
parse_polars_error::<&str>(&e, &args.call_info.name_tag.span, None)
})?;
casted.contains(pat).map_err(|e| {
parse_polars_error::<&str>(&e, &args.call_info.name_tag.span, None)
})
}
_ => Err(ShellError::labeled_error_with_secondary(
"Incorrect argument",
"Can't perform contains with this value",
&rhs.tag.span,
"Contains only works with strings",
&rhs.tag.span,
)),
},
_ => Err(ShellError::labeled_error_with_secondary(
"Incorrect datatype",
format!("The selected column is of type '{}'", col.dtype()),
col_name_span,
"Perhaps you want to select a column of 'str' type",
col_name_span,
)),
},
_ => Err(ShellError::labeled_error(
"Incorrect operator",
"Not implemented operator for dataframes filter",

9
crates/nu-data/Cargo.toml
View File

@ -37,10 +37,17 @@ nu-test-support = { version = "0.32.1", path = "../nu-test-support" }
nu-value-ext = { version = "0.32.1", path = "../nu-value-ext" }
nu-ansi-term = { version = "0.32.1", path = "../nu-ansi-term" }
[dependencies.polars]
git = "https://github.com/pola-rs/polars"
rev = "9e1506cca9fb646fc55f949ab6345290c3d198a7"
version = "0.14.1"
optional = true
features = ["strings", "checked_arithmetic"]
[target.'cfg(unix)'.dependencies]
users = "0.11.0"
[features]
directories = ["directories-next"]
dirs = ["dirs-next"]
dataframe = ["nu-protocol/dataframe"]
dataframe = ["nu-protocol/dataframe", "polars"]

717
crates/nu-data/src/dataframe.rs Normal file
View File

@ -0,0 +1,717 @@
use bigdecimal::BigDecimal;
use nu_errors::ShellError;
use nu_protocol::hir::Operator;
use nu_protocol::{
dataframe::{NuSeries, PolarsData},
Primitive, ShellTypeName, UntaggedValue, Value,
};
use nu_source::Span;
use num_traits::ToPrimitive;
use num_bigint::BigInt;
use polars::prelude::{
BooleanType, ChunkCompare, ChunkedArray, DataType, Float64Type, Int64Type, IntoSeries,
NumOpsDispatchChecked, Series,
};
use std::ops::{Add, BitAnd, BitOr, Div, Mul, Sub};
pub fn compute_between_series(
operator: Operator,
left: &Value,
right: &Value,
) -> Result<UntaggedValue, (&'static str, &'static str)> {
if let (
UntaggedValue::DataFrame(PolarsData::Series(lhs)),
UntaggedValue::DataFrame(PolarsData::Series(rhs)),
) = (&left.value, &right.value)
{
if lhs.as_ref().dtype() != rhs.as_ref().dtype() {
return Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Mixed datatypes",
"this datatype does not match the right hand side datatype",
&left.tag.span,
format!(
"Perhaps you want to change this datatype to '{}'",
lhs.as_ref().dtype()
),
&right.tag.span,
),
));
}
if lhs.as_ref().len() != rhs.as_ref().len() {
return Ok(UntaggedValue::Error(ShellError::labeled_error(
"Different length",
"this column length does not match the right hand column length",
&left.tag.span,
)));
}
match operator {
Operator::Plus => {
let mut res = lhs.as_ref() + rhs.as_ref();
let name = format!("sum_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::Minus => {
let mut res = lhs.as_ref() - rhs.as_ref();
let name = format!("sub_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::Multiply => {
let mut res = lhs.as_ref() * rhs.as_ref();
let name = format!("mul_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::Divide => {
let res = lhs.as_ref().checked_div(rhs.as_ref());
match res {
Ok(mut res) => {
let name = format!("div_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Err(e) => Ok(UntaggedValue::Error(ShellError::labeled_error(
"Division error",
format!("{}", e),
&left.tag.span,
))),
}
}
Operator::Equal => {
let mut res = Series::eq(lhs.as_ref(), rhs.as_ref()).into_series();
let name = format!("eq_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::NotEqual => {
let mut res = Series::neq(lhs.as_ref(), rhs.as_ref()).into_series();
let name = format!("neq_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::LessThan => {
let mut res = Series::lt(lhs.as_ref(), rhs.as_ref()).into_series();
let name = format!("lt_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::LessThanOrEqual => {
let mut res = Series::lt_eq(lhs.as_ref(), rhs.as_ref()).into_series();
let name = format!("lte_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::GreaterThan => {
let mut res = Series::gt(lhs.as_ref(), rhs.as_ref()).into_series();
let name = format!("gt_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::GreaterThanOrEqual => {
let mut res = Series::gt_eq(lhs.as_ref(), rhs.as_ref()).into_series();
let name = format!("gte_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
Operator::And => match lhs.as_ref().dtype() {
DataType::Boolean => {
let lhs_cast = lhs.as_ref().bool();
let rhs_cast = rhs.as_ref().bool();
match (lhs_cast, rhs_cast) {
(Ok(l), Ok(r)) => {
let mut res = l.bitand(r).into_series();
let name =
format!("and_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Casting error",
"unable to cast to boolean",
&left.tag.span,
"unable to cast to boolean",
&right.tag.span,
),
)),
}
}
_ => Ok(UntaggedValue::Error(ShellError::labeled_error(
"Incorrect datatype",
"And operation can only be done with boolean values",
&left.tag.span,
))),
},
Operator::Or => match lhs.as_ref().dtype() {
DataType::Boolean => {
let lhs_cast = lhs.as_ref().bool();
let rhs_cast = rhs.as_ref().bool();
match (lhs_cast, rhs_cast) {
(Ok(l), Ok(r)) => {
let mut res = l.bitor(r).into_series();
let name =
format!("or_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
res.rename(name.as_ref());
Ok(NuSeries::series_to_untagged(res))
}
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Casting error",
"unable to cast to boolean",
&left.tag.span,
"unable to cast to boolean",
&right.tag.span,
),
)),
}
}
_ => Ok(UntaggedValue::Error(ShellError::labeled_error(
"Incorrect datatype",
"And operation can only be done with boolean values",
&left.tag.span,
))),
},
_ => Ok(UntaggedValue::Error(ShellError::labeled_error(
"Incorrect datatype",
"unable to use this datatype for this operation",
&left.tag.span,
))),
}
} else {
Err((left.type_name(), right.type_name()))
}
}
pub fn compute_series_single_value(
operator: Operator,
left: &Value,
right: &Value,
) -> Result<UntaggedValue, (&'static str, &'static str)> {
if let (UntaggedValue::DataFrame(PolarsData::Series(lhs)), UntaggedValue::Primitive(_)) =
(&left.value, &right.value)
{
match operator {
Operator::Plus => match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compute_series_i64(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::add,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compute_series_bigint(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::add,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(compute_series_decimal(
lhs.as_ref(),
val,
<&ChunkedArray<Float64Type>>::add,
&left.tag.span,
)),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to sum this value to the series",
&right.tag.span,
"Only int, bigInt or decimal values are allowed",
&right.tag.span,
),
)),
},
Operator::Minus => match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compute_series_i64(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::sub,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compute_series_bigint(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::sub,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(compute_series_decimal(
lhs.as_ref(),
val,
<&ChunkedArray<Float64Type>>::sub,
&left.tag.span,
)),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to subtract this value to the series",
&right.tag.span,
"Only int, bigInt or decimal values are allowed",
&right.tag.span,
),
)),
},
Operator::Multiply => match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compute_series_i64(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::mul,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compute_series_bigint(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::mul,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(compute_series_decimal(
lhs.as_ref(),
val,
<&ChunkedArray<Float64Type>>::mul,
&left.tag.span,
)),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to multiply this value to the series",
&right.tag.span,
"Only int, bigInt or decimal values are allowed",
&right.tag.span,
),
)),
},
Operator::Divide => match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => {
if *val == 0 {
Ok(UntaggedValue::Error(ShellError::labeled_error(
"Division by zero",
"Zero value found",
&right.tag.span,
)))
} else {
Ok(compute_series_i64(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::div,
&left.tag.span,
))
}
}
UntaggedValue::Primitive(Primitive::BigInt(val)) => {
if val.eq(&0.into()) {
Ok(UntaggedValue::Error(ShellError::labeled_error(
"Division by zero",
"Zero value found",
&right.tag.span,
)))
} else {
Ok(compute_series_bigint(
lhs.as_ref(),
val,
<&ChunkedArray<Int64Type>>::div,
&left.tag.span,
))
}
}
UntaggedValue::Primitive(Primitive::Decimal(val)) => {
if val.eq(&0.into()) {
Ok(UntaggedValue::Error(ShellError::labeled_error(
"Division by zero",
"Zero value found",
&right.tag.span,
)))
} else {
Ok(compute_series_decimal(
lhs.as_ref(),
val,
<&ChunkedArray<Float64Type>>::div,
&left.tag.span,
))
}
}
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to divide this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
},
Operator::Equal => {
match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compare_series_i64(
lhs.as_ref(),
val,
ChunkedArray::eq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compare_series_bigint(
lhs.as_ref(),
val,
ChunkedArray::eq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(
compare_series_decimal(lhs.as_ref(), val, ChunkedArray::eq, &left.tag.span),
),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to compare this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
}
}
Operator::NotEqual => match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compare_series_i64(
lhs.as_ref(),
val,
ChunkedArray::neq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compare_series_bigint(
lhs.as_ref(),
val,
ChunkedArray::neq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(compare_series_decimal(
lhs.as_ref(),
val,
ChunkedArray::neq,
&left.tag.span,
)),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to compare this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
},
Operator::LessThan => {
match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compare_series_i64(
lhs.as_ref(),
val,
ChunkedArray::lt,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compare_series_bigint(
lhs.as_ref(),
val,
ChunkedArray::lt,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(
compare_series_decimal(lhs.as_ref(), val, ChunkedArray::lt, &left.tag.span),
),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to compare this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
}
}
Operator::LessThanOrEqual => match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compare_series_i64(
lhs.as_ref(),
val,
ChunkedArray::lt_eq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compare_series_bigint(
lhs.as_ref(),
val,
ChunkedArray::lt_eq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(compare_series_decimal(
lhs.as_ref(),
val,
ChunkedArray::lt_eq,
&left.tag.span,
)),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to compare this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
},
Operator::GreaterThan => {
match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compare_series_i64(
lhs.as_ref(),
val,
ChunkedArray::gt,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compare_series_bigint(
lhs.as_ref(),
val,
ChunkedArray::gt,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(
compare_series_decimal(lhs.as_ref(), val, ChunkedArray::gt, &left.tag.span),
),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to compare this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
}
}
Operator::GreaterThanOrEqual => match &right.value {
UntaggedValue::Primitive(Primitive::Int(val)) => Ok(compare_series_i64(
lhs.as_ref(),
val,
ChunkedArray::gt_eq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::BigInt(val)) => Ok(compare_series_bigint(
lhs.as_ref(),
val,
ChunkedArray::gt_eq,
&left.tag.span,
)),
UntaggedValue::Primitive(Primitive::Decimal(val)) => Ok(compare_series_decimal(
lhs.as_ref(),
val,
ChunkedArray::gt_eq,
&left.tag.span,
)),
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to compare this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
},
Operator::Contains => match &right.value {
UntaggedValue::Primitive(Primitive::String(val)) => {
Ok(contains_series_pat(lhs.as_ref(), val, &left.tag.span))
}
_ => Ok(UntaggedValue::Error(
ShellError::labeled_error_with_secondary(
"Operation unavailable",
"unable to perform this value to the series",
&right.tag.span,
"Only primary values are allowed",
&right.tag.span,
),
)),
},
_ => Ok(UntaggedValue::Error(ShellError::labeled_error(
"Incorrect datatype",
"unable to use this value for this operation",
&left.tag.span,
))),
}
} else {
Err((left.type_name(), right.type_name()))
}
}
fn compute_series_i64<'r, F>(series: &'r Series, val: &i64, f: F, span: &Span) -> UntaggedValue
where
F: Fn(&'r ChunkedArray<Int64Type>, i64) -> ChunkedArray<Int64Type>,
{
let casted = series.i64();
match casted {
Ok(casted) => {
let res = f(casted, *val);
let res = res.into_series();
NuSeries::series_to_untagged(res)
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Casting error",
format!("{}", e),
span,
)),
}
}
fn compute_series_bigint<'r, F>(
series: &'r Series,
val: &BigInt,
f: F,
span: &Span,
) -> UntaggedValue
where
F: Fn(&'r ChunkedArray<Int64Type>, i64) -> ChunkedArray<Int64Type>,
{
let casted = series.i64();
match casted {
Ok(casted) => {
let res = f(
casted,
val.to_i64()
.expect("Internal error: protocol did not use compatible decimal"),
);
let res = res.into_series();
NuSeries::series_to_untagged(res)
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Casting error",
format!("{}", e),
span,
)),
}
}
fn compute_series_decimal<'r, F>(
series: &'r Series,
val: &BigDecimal,
f: F,
span: &Span,
) -> UntaggedValue
where
F: Fn(&'r ChunkedArray<Float64Type>, f64) -> ChunkedArray<Float64Type>,
{
let casted = series.f64();
match casted {
Ok(casted) => {
let res = f(
casted,
val.to_f64()
.expect("Internal error: protocol did not use compatible decimal"),
);
let res = res.into_series();
NuSeries::series_to_untagged(res)
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Casting error",
format!("{}", e),
span,
)),
}
}
fn compare_series_i64<'r, F>(series: &'r Series, val: &i64, f: F, span: &Span) -> UntaggedValue
where
F: Fn(&'r ChunkedArray<Int64Type>, i64) -> ChunkedArray<BooleanType>,
{
let casted = series.i64();
match casted {
Ok(casted) => {
let res = f(casted, *val);
let res = res.into_series();
NuSeries::series_to_untagged(res)
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Casting error",
format!("{}", e),
span,
)),
}
}
fn compare_series_bigint<'r, F>(
series: &'r Series,
val: &BigInt,
f: F,
span: &Span,
) -> UntaggedValue
where
F: Fn(&'r ChunkedArray<Int64Type>, i64) -> ChunkedArray<BooleanType>,
{
let casted = series.i64();
match casted {
Ok(casted) => {
let res = f(
casted,
val.to_i64()
.expect("Internal error: protocol did not use compatible decimal"),
);
let res = res.into_series();
NuSeries::series_to_untagged(res)
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Casting error",
format!("{}", e),
span,
)),
}
}
fn compare_series_decimal<'r, F>(
series: &'r Series,
val: &BigDecimal,
f: F,
span: &Span,
) -> UntaggedValue
where
F: Fn(&'r ChunkedArray<Float64Type>, i64) -> ChunkedArray<BooleanType>,
{
let casted = series.f64();
match casted {
Ok(casted) => {
let res = f(
casted,
val.to_i64()
.expect("Internal error: protocol did not use compatible decimal"),
);
let res = res.into_series();
NuSeries::series_to_untagged(res)
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Casting error",
format!("{}", e),
span,
)),
}
}
fn contains_series_pat(series: &Series, pat: &str, span: &Span) -> UntaggedValue {
let casted = series.utf8();
match casted {
Ok(casted) => {
let res = casted.contains(pat);
match res {
Ok(res) => {
let res = res.into_series();
NuSeries::series_to_untagged(res)
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Search error",
format!("{}", e),
span,
)),
}
}
Err(e) => UntaggedValue::Error(ShellError::labeled_error(
"Casting error",
format!("{}", e),
span,
)),
}
}

3
crates/nu-data/src/lib.rs
View File

@ -7,4 +7,7 @@ pub mod types;
pub mod utils;
pub mod value;
#[cfg(feature = "dataframe")]
pub mod dataframe;
pub use dict::TaggedListBuilder;

48
crates/nu-data/src/value.rs
View File

@ -12,9 +12,6 @@ use num_bigint::BigInt;
use num_traits::{ToPrimitive, Zero};
use std::collections::HashMap;
#[cfg(feature = "dataframe")]
use nu_protocol::dataframe::{NuSeries, PolarsData};
pub struct Date;
impl Date {
@ -494,51 +491,6 @@ pub fn compute_values(
}
_ => Err((left.type_name(), right.type_name())),
},
#[cfg(feature = "dataframe")]
(
UntaggedValue::DataFrame(PolarsData::Series(lhs)),
UntaggedValue::DataFrame(PolarsData::Series(rhs)),
) => {
if lhs.as_ref().dtype() == rhs.as_ref().dtype() {
let result = match operator {
Operator::Plus => {
let mut res = lhs.as_ref() + rhs.as_ref();
let name = format!("sum_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
let res = res.rename(name.as_ref());
Ok(res.clone())
}
Operator::Minus => {
let mut res = lhs.as_ref() - rhs.as_ref();
let name = format!("sub_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
let res = res.rename(name.as_ref());
Ok(res.clone())
}
Operator::Multiply => {
let mut res = lhs.as_ref() * rhs.as_ref();
let name = format!("mul_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
let res = res.rename(name.as_ref());
Ok(res.clone())
}
Operator::Divide => {
let mut res = lhs.as_ref() / rhs.as_ref();
let name = format!("div_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
let res = res.rename(name.as_ref());
Ok(res.clone())
}
Operator::Modulo => {
let mut res = lhs.as_ref() % rhs.as_ref();
let name = format!("mod_{}_{}", lhs.as_ref().name(), rhs.as_ref().name());
let res = res.rename(name.as_ref());
Ok(res.clone())
}
_ => Err((left.type_name(), right.type_name())),
}?;
Ok(NuSeries::series_to_untagged(result))
} else {
Err((left.type_name(), right.type_name()))
}
}
_ => Err((left.type_name(), right.type_name())),
}
}

1
crates/nu-engine/Cargo.toml
View File

@ -65,3 +65,4 @@ hamcrest2 = "0.3.0"
rustyline-support = []
dirs = ["dirs-next"]
trash-support = ["trash"]
dataframe = ["nu-protocol/dataframe"]

18
crates/nu-engine/src/evaluate/operator.rs
View File

@ -4,11 +4,29 @@ use nu_protocol::hir::Operator;
use nu_protocol::{Primitive, ShellTypeName, UntaggedValue, Value};
use std::ops::Not;
#[cfg(feature = "dataframe")]
use nu_data::dataframe::{compute_between_series, compute_series_single_value};
#[cfg(feature = "dataframe")]
use nu_protocol::dataframe::PolarsData;
pub fn apply_operator(
op: Operator,
left: &Value,
right: &Value,
) -> Result<UntaggedValue, (&'static str, &'static str)> {
#[cfg(feature = "dataframe")]
if let (
UntaggedValue::DataFrame(PolarsData::Series(_)),
UntaggedValue::DataFrame(PolarsData::Series(_)),
) = (&left.value, &right.value)
{
return compute_between_series(op, left, right);
} else if let (UntaggedValue::DataFrame(PolarsData::Series(_)), UntaggedValue::Primitive(_)) =
(&left.value, &right.value)
{
return compute_series_single_value(op, left, right);
}
match op {
Operator::Equal
| Operator::NotEqual

6
crates/nu-protocol/Cargo.toml
View File

@ -32,10 +32,10 @@ toml = "0.5.8"
[dependencies.polars]
git = "https://github.com/pola-rs/polars"
rev = "a5f17b0a6e3e05ff6be789aa24a7cae54fd400dd"
version = "0.14.0"
rev = "9e1506cca9fb646fc55f949ab6345290c3d198a7"
version = "0.14.1"
optional = true
features = ["serde"]
features = ["serde", "rows"]
[features]
dataframe = ["polars"]

2
crates/nu-protocol/src/dataframe/nu_dataframe.rs
View File

@ -185,7 +185,7 @@ impl NuDataFrame {
}
pub fn to_rows(&self, from_row: usize, to_row: usize) -> Result<Vec<Value>, ShellError> {
let df = &self.as_ref();
let df = self.as_ref();
let column_names = df.get_column_names();
let mut values: Vec<Value> = Vec::new();