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https://github.com/jrasband-dev/polars-extensions


https://github.com/jrasband-dev/polars-extensions

dataframe polars polars-dataframe polars-extensions polars-plugins pypi python

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# Polars Extensions

![alt text](https://raw.githubusercontent.com/jrasband-dev/polars-extensions/refs/heads/main/plx.svg)

[![PyPI version](https://img.shields.io/pypi/v/polars-extensions.svg)](https://pypi.org/project/polars-extensions/)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)
[![Documentation Status](https://img.shields.io/badge/docs-online-brightgreen.svg)](https://jrasband-dev.github.io/polars-extensions/)


For full details and usage, see the [official documentation](https://jrasband-dev.github.io/polars-extensions/).

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## Getting Started

```bash
pip install polars-extensions
```

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## Why use Polars Extensions?

Polars Extensions fills in widely used convenience functions and transformations that many data workflows rely on — without needing custom ad-hoc code. Whether you need to:

- Read or write schema definitions to manage data structure programmatically
- Convert between number formats (e.g. numbers ↔ Roman numerals, parse textual numbers)
- Uniformly rename columns across naming conventions (snake_case, camelCase, kebab-case, PascalCase, etc.)
- Compute approximate string-similarity (F1 similarity) for fuzzy matching or cleanup
- Work with simple geospatial transformations (e.g. WKT/WKB ↔ coordinate formats)

Polars Extensions provides a clean, expressive, and consistent API (using Polars expression namespaces) so you stay in the “Polars way” of data manipulation.