Melts

Melt operations unpivot a DataFrame from wide format to long format

Dataset

Python Rust

DataFrame

import polars as pl

df = pl.DataFrame(
    {
        "A": ["a", "b", "a"],
        "B": [1, 3, 5],
        "C": [10, 11, 12],
        "D": [2, 4, 6],
    }
)
print(df)

DataFrame

let df = df!(
        "A"=> &["a", "b", "a"],
        "B"=> &[1, 3, 5],
        "C"=> &[10, 11, 12],
        "D"=> &[2, 4, 6],
)?;
println!("{}", &df);

shape: (3, 4)
┌─────┬─────┬─────┬─────┐
│ A   ┆ B   ┆ C   ┆ D   │
│ --- ┆ --- ┆ --- ┆ --- │
│ str ┆ i64 ┆ i64 ┆ i64 │
╞═════╪═════╪═════╪═════╡
│ a   ┆ 1   ┆ 10  ┆ 2   │
│ b   ┆ 3   ┆ 11  ┆ 4   │
│ a   ┆ 5   ┆ 12  ┆ 6   │
└─────┴─────┴─────┴─────┘

Eager + lazy

Eager and lazy have the same API.

Python Rust

melt

out = df.melt(id_vars=["A", "B"], value_vars=["C", "D"])
print(out)

let out = df.melt(["A", "B"], ["C", "D"])?;
println!("{}", &out);

shape: (6, 4)
┌─────┬─────┬──────────┬───────┐
│ A   ┆ B   ┆ variable ┆ value │
│ --- ┆ --- ┆ ---      ┆ ---   │
│ str ┆ i64 ┆ str      ┆ i64   │
╞═════╪═════╪══════════╪═══════╡
│ a   ┆ 1   ┆ C        ┆ 10    │
│ b   ┆ 3   ┆ C        ┆ 11    │
│ a   ┆ 5   ┆ C        ┆ 12    │
│ a   ┆ 1   ┆ D        ┆ 2     │
│ b   ┆ 3   ┆ D        ┆ 4     │
│ a   ┆ 5   ┆ D        ┆ 6     │
└─────┴─────┴──────────┴───────┘