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feat(polars): add polars horizontal
aggregation command (#15656)
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@ -0,0 +1,191 @@
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use crate::{
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values::{Column, CustomValueSupport, NuDataFrame, NuExpression},
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PolarsPlugin,
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};
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use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
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use nu_protocol::{
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Category, Example, LabeledError, PipelineData, ShellError, Signature, Span, Spanned,
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SyntaxShape, Type, Value,
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};
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use polars::lazy::dsl::{
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all_horizontal, any_horizontal, max_horizontal, mean_horizontal, min_horizontal, sum_horizontal,
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};
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use polars::prelude::Expr;
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enum HorizontalType {
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All,
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Any,
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Min,
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Max,
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Sum,
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Mean,
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}
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impl HorizontalType {
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fn from_str(roll_type: &str, span: Span) -> Result<Self, ShellError> {
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match roll_type {
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"all" => Ok(Self::All),
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"any" => Ok(Self::Any),
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"min" => Ok(Self::Min),
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"max" => Ok(Self::Max),
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"sum" => Ok(Self::Sum),
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"mean" => Ok(Self::Mean),
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_ => Err(ShellError::GenericError {
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error: "Wrong operation".into(),
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msg: "Operation not valid for cumulative".into(),
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span: Some(span),
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help: Some("Allowed values: all, any, max, min, sum, mean".into()),
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inner: vec![],
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}),
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}
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}
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}
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#[derive(Clone)]
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pub struct Horizontal;
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impl PluginCommand for Horizontal {
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type Plugin = PolarsPlugin;
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fn name(&self) -> &str {
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"polars horizontal"
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}
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fn description(&self) -> &str {
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"Horizontal calculation across multiple columns."
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}
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fn signature(&self) -> Signature {
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Signature::build(self.name())
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.input_output_type(Type::Any, Type::Custom("expression".into()))
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.required(
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"type",
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SyntaxShape::String,
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"horizontal operation. Values of all, any, min, max, sum, and mean are accepted.",
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)
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.rest(
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"Group-by expressions",
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SyntaxShape::Any,
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"Expression(s) that define the lazy group-by",
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)
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.switch(
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"nulls",
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"If set, null value in the input will lead to null output",
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Some('n'),
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)
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.category(Category::Custom("expression".into()))
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}
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fn examples(&self) -> Vec<Example> {
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vec![
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Example {
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description: "Horizontal sum across two columns (ignore nulls by default)",
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example: "[[a b]; [1 2] [2 3] [3 4] [4 5] [5 null]]
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| polars into-df
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| polars select (polars horizontal sum a b)
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| polars collect",
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result: Some(
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NuDataFrame::try_from_columns(
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vec![Column::new(
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"sum".to_string(),
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vec![
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Value::test_int(3),
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Value::test_int(5),
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Value::test_int(7),
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Value::test_int(9),
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Value::test_int(5),
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],
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)],
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None,
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)
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.expect("simple df for test should not fail")
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.into_value(Span::test_data()),
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),
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},
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Example {
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description: "Horizontal sum across two columns while accounting for nulls",
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example: "[[a b]; [1 2] [2 3] [3 4] [4 5] [5 null]]
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| polars into-df
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| polars select (polars horizontal sum a b --nulls)
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| polars collect",
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result: Some(
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NuDataFrame::try_from_columns(
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vec![Column::new(
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"sum".to_string(),
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vec![
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Value::test_int(3),
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Value::test_int(5),
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Value::test_int(7),
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Value::test_int(9),
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Value::test_nothing(),
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],
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)],
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None,
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)
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.expect("simple df for test should not fail")
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.into_value(Span::test_data()),
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),
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},
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]
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}
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fn run(
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&self,
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plugin: &Self::Plugin,
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engine: &EngineInterface,
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call: &EvaluatedCall,
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_input: PipelineData,
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) -> Result<PipelineData, LabeledError> {
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let func_type: Spanned<String> = call.req(0)?;
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let func_type = HorizontalType::from_str(&func_type.item, func_type.span)?;
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let vals: Vec<Value> = call.rest(1)?;
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let expr_value = Value::list(vals, call.head);
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let exprs = NuExpression::extract_exprs(plugin, expr_value)?;
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let ignore_nulls = !call.has_flag("nulls")?;
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command(plugin, engine, call, func_type, exprs, ignore_nulls).map_err(LabeledError::from)
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}
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}
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fn command(
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plugin: &PolarsPlugin,
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engine: &EngineInterface,
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call: &EvaluatedCall,
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func_type: HorizontalType,
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exprs: Vec<Expr>,
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ignore_nulls: bool,
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) -> Result<PipelineData, ShellError> {
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let res: NuExpression = match func_type {
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HorizontalType::All => all_horizontal(exprs),
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HorizontalType::Any => any_horizontal(exprs),
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HorizontalType::Max => max_horizontal(exprs),
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HorizontalType::Min => min_horizontal(exprs),
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HorizontalType::Sum => sum_horizontal(exprs, ignore_nulls),
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HorizontalType::Mean => mean_horizontal(exprs, ignore_nulls),
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}
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.map_err(|e| ShellError::GenericError {
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error: "Cannot apply horizontal aggregation".to_string(),
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msg: "".into(),
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span: Some(call.head),
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help: Some(e.to_string()),
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inner: vec![],
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})?
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.into();
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res.to_pipeline_data(plugin, engine, call.head)
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}
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#[cfg(test)]
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mod test {
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use super::*;
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use crate::test::test_polars_plugin_command;
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#[test]
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fn test_examples() -> Result<(), ShellError> {
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test_polars_plugin_command(&Horizontal)
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}
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}
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@ -3,6 +3,7 @@ mod aggregate;
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mod count;
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mod cumulative;
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pub mod groupby;
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mod horizontal;
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mod implode;
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mod max;
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mod mean;
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@ -25,6 +26,7 @@ use nu_plugin::PluginCommand;
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pub use aggregate::LazyAggregate;
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use count::ExprCount;
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pub use cumulative::Cumulative;
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pub use horizontal::Horizontal;
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use implode::ExprImplode;
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use max::ExprMax;
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use mean::ExprMean;
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@ -45,19 +47,20 @@ pub(crate) fn aggregation_commands() -> Vec<Box<dyn PluginCommand<Plugin = Polar
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Box::new(ExprCount),
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Box::new(ExprImplode),
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Box::new(ExprMax),
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Box::new(ExprMin),
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Box::new(ExprSum),
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Box::new(ExprMean),
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Box::new(ExprMin),
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Box::new(ExprStd),
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Box::new(ExprSum),
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Box::new(ExprVar),
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Box::new(Horizontal),
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Box::new(LazyAggregate),
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Box::new(median::LazyMedian),
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Box::new(quantile::LazyQuantile),
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Box::new(groupby::ToLazyGroupBy),
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Box::new(NNull),
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Box::new(NUnique),
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Box::new(Over),
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Box::new(Rolling),
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Box::new(ValueCount),
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Box::new(NNull),
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Box::new(NUnique),
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Box::new(groupby::ToLazyGroupBy),
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Box::new(median::LazyMedian),
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Box::new(quantile::LazyQuantile),
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]
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}
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