Files
nushell/crates/nu-cmd-dataframe/src/dataframe/expressions/when.rs
Jack Wright f879c00f9d The ability to specify a schema when using dfr open and dfr into-df (#11634)
# Description

There are times where explicitly specifying a schema for a dataframe is
needed such as:
- Opening CSV and JSON lines files and needing provide more information
to polars to keep it from failing or in a desire to override default
type conversion
- When converting a nushell value to a dataframe and wanting to override
the default conversion behaviors.

This pull requests provides:
- A flag to allow specifying a schema when using dfr into-df
- A flag to allow specifying a schema when using dfr open that works for
CSV and JSON types
- A new command `dfr schema` which displays schema information and will
allow display support schema dtypes

Schema is specified creating a record that has the key value and the
dtype. Examples usages:

```
{a:1, b:{a:2}} | dfr into-df -s {a: u8, b: {a: i32}} | dfr schema
{a: 1, b: {a: [1 2 3]}, c: [a b c]} | dfr into-df -s {a: u8, b: {a: list<u64>}, c: list<str>} | dfr schema
 dfr open -s {pid: i32, ppid: i32, name: str, status: str, cpu: f64, mem: i64, virtual: i64} /tmp/ps.jsonl  | dfr schema
```

Supported dtypes:
null                                                   
bool                                                   
u8                                                     
u16                                                    
u32                                                    
u64                                                    
i8                                                     
i16                                                    
i32                                                    
i64                                                    
f32                                                    
f64                                                    
str                                                    
binary                                                 
date                                                   
datetime[time_unit: (ms, us, ns) timezone (optional)]  
duration[time_unit: (ms, us, ns)]                      
time                                                   
object                                                 
unknown                                                
list[dtype]


structs are also supported but are specified via another record:
{a: u8, b: {d: str}}

Another feature with the dfr schema command is that it returns the data
back in a format that can be passed to provide a valid schema that can
be passed in as schema argument:

<img width="638" alt="Screenshot 2024-01-29 at 10 23 58"
src="https://github.com/nushell/nushell/assets/56345/b49c3bff-5cda-4c86-975a-dfd91d991373">

---------

Co-authored-by: Jack Wright <jack.wright@disqo.com>
2024-01-29 13:26:04 -06:00

152 lines
5.1 KiB
Rust

use crate::dataframe::values::{Column, NuDataFrame, NuExpression, NuWhen};
use nu_engine::CallExt;
use nu_protocol::{
ast::Call,
engine::{Command, EngineState, Stack},
Category, Example, PipelineData, ShellError, Signature, Span, SyntaxShape, Type, Value,
};
use polars::prelude::when;
#[derive(Clone)]
pub struct ExprWhen;
impl Command for ExprWhen {
fn name(&self) -> &str {
"dfr 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: "dfr when ((dfr col a) > 2) 4",
result: None,
},
Example {
description: "Create a when conditions",
example: "dfr when ((dfr col a) > 2) 4 | dfr when ((dfr 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]]
| dfr into-lazy
| dfr with-column (
dfr when ((dfr col a) > 2) 4 | dfr otherwise 5 | dfr as c
)
| dfr with-column (
dfr when ((dfr col a) > 5) 10 | dfr when ((dfr col a) < 2) 6 | dfr otherwise 0 | dfr as d
)
| dfr 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,
engine_state: &EngineState,
stack: &mut Stack,
call: &Call,
input: PipelineData,
) -> Result<PipelineData, ShellError> {
let when_predicate: Value = call.req(engine_state, stack, 0)?;
let when_predicate = NuExpression::try_from_value(when_predicate)?;
let then_predicate: Value = call.req(engine_state, stack, 1)?;
let then_predicate = NuExpression::try_from_value(then_predicate)?;
let value = input.into_value(call.head);
let when_then: NuWhen = match value {
Value::Nothing { .. } => when(when_predicate.into_polars())
.then(then_predicate.into_polars())
.into(),
v => match NuWhen::try_from_value(v)? {
NuWhen::Then(when_then) => when_then
.when(when_predicate.into_polars())
.then(then_predicate.into_polars())
.into(),
NuWhen::ChainedThen(when_then_then) => when_then_then
.when(when_predicate.into_polars())
.then(then_predicate.into_polars())
.into(),
},
};
Ok(PipelineData::Value(when_then.into_value(call.head), None))
}
}
#[cfg(test)]
mod test {
use super::super::super::test_dataframe::test_dataframe;
use crate::dataframe::eager::{ToNu, WithColumn};
use crate::dataframe::expressions::otherwise::ExprOtherwise;
use crate::dataframe::expressions::{ExprAlias, ExprCol};
use super::*;
#[test]
fn test_examples() {
test_dataframe(vec![
Box::new(WithColumn {}),
Box::new(ExprCol {}),
Box::new(ExprAlias {}),
Box::new(ExprWhen {}),
Box::new(ExprOtherwise {}),
Box::new(ToNu {}),
])
}
}