polars_ethan 0.2.4

Fast Polars functions that Ethan likes to use.

polars-ethan is a Python library that adds useful functions for use with Polars. This is also my first published package, so it is a good exercsie.

Features

Demean

The demean function subtracts the mean from each non-NaN value in an array, preserving NaN values.

import polars as pl
from ethanpolars import demean

# Sample data...
cameras = pl.DataFrame(
    {
        "brand": ["Leica", "Leica", "Leica", "Mamiya", "Mamiya", "Mamiya"],
        "model": ["MP", "M4", "M7", "RB67", "7II", "645 Pro"],
        "price": [6000, 10000, None, 600, 3000, 900],
    }
)

cameras = cameras.with_columns(
    pl.col('price')
    .fill_null(np.nan)
    .map_batches(demean)
    .over(pl.col("brand"))
    .fill_nan(None)
    .alias('d_price')
)

print(cameras)

Output:

┌────────┬─────────┬───────┬─────────┐
│ brand  ┆ model   ┆ price ┆ d_price │
│ ---    ┆ ---     ┆ ---   ┆ ---     │
│ str    ┆ str     ┆ i64   ┆ f64     │
╞════════╪═════════╪═══════╪═════════╡
│ Leica  ┆ MP      ┆ 6000  ┆ -2000.0 │
│ Leica  ┆ M4      ┆ 10000 ┆ 2000.0  │
│ Leica  ┆ M7      ┆ null  ┆ null    │
│ Mamiya ┆ RB67    ┆ 600   ┆ -900.0  │
│ Mamiya ┆ 7II     ┆ 3000  ┆ 1500.0  │
│ Mamiya ┆ 645 Pro ┆ 900   ┆ -600.0  │
└────────┴─────────┴───────┴─────────┘

Note how null values must be converted to NaN before being passed to the function. Generalized ufuncs do not except null values, but NaN's are fine and behave how we like.