polars-ols

library0.3.5pypypi✓ verified 82d ago

An extension for Polars providing Ordinary Least Squares (OLS) regression support. Version 0.3.5 is current. Release cadence is irregular.

analytics

pip install polars-ols

INSTALL

IMPORT

SIG · POLARS-OLS

polars-ols

analyticspythonv0.3.5

harness data pending

Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

least_squares

✓ from polars_ols import least_squares

✗ from polars_ols import OLS

compute_least_squares

✓ from polars_ols import compute_least_squares

LeastSquares

✓ from polars_ols import LeastSquares

Fit OLS regression using polars-pipe syntax.

import polars as pl import polars_ols df = pl.DataFrame({ 'y': [1.0, 2.0, 3.0, 4.0, 5.0], 'x1': [2.0, 3.0, 4.0, 5.0, 6.0], 'x2': [1.0, 4.0, 9.0, 16.0, 25.0] }) result = df.pipe(polars_ols.ols, 'y', ['x1', 'x2']) print(result)

Debug

Known issues

gotchaThe package provides a single function `ols`; it does not support multiple regression types or complex formulas.

fix

Use polars_ols.ols for linear OLS only. For other models, consider statsmodel or sklearn.

affects: all

gotchaThe function returns a polars DataFrame with columns for coefficients, standard errors, t-stats, p-values, etc., not a statsmodels-like result object.

fix

Access results via DataFrame column names, e.g., result['coef'].

affects: all

deprecatedInterface changed in 0.3.0: previously used `polars_ols.ols(df, y, x)` now uses `df.pipe(polars_ols.ols, y, x)`.

fix

Use pipe syntax: df.pipe(polars_ols.ols, 'y', ['x1', 'x2'])

affects: <0.3.0

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Version history

0.3.5latest on PyPI · released Aug 25, 2024

Audit

Dependencies

polarsrequiredCore dependency for dataframe operations

Agent activity

31 hits · last 30 days

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OpenAI (training)

Resources

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