nushell/crates/nu_plugin_polars/src/dataframe/eager/melt.rs
Ian Manske 84b7a99adf
Revert "Polars lazy refactor (#12669)" (#12962)
This reverts commit 68adc4657f.

# Description

Reverts the lazyframe refactor (#12669) for the next release, since
there are still a few lingering issues. This temporarily solves #12863
and #12828. After the release, the lazyframes can be added back and
cleaned up.
2024-05-24 18:09:26 -05:00

254 lines
8.1 KiB
Rust

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::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_coerce(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);
res.to_pipeline_data(plugin, engine, call.head)
}
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)
}
}