Polars Vec Ops

A Polars plugin for vertical operations on columns 1D arrays or lists of equal length - aggregate across rows instead of within lists.

🚧 Under Development

⚠️ Disclaimer: The initial Rust extensions are entirely AI-generated, as are the majority of tests and documentation. Use at your own risk!

Acknowledgments

Initialized from https://github.com/MarcoGorelli/cookiecutter-polars-plugins: thanks to Marco Gorelli for writing the excellent Polars Plugins Tutorial.

Installation

uv add polars-vec-ops

Quick Start

>>> import polars as pl
>>> import polars_vec_ops # registers the `vec` namespace on columns/expressions
>>> df = pl.DataFrame({"a": [[1, 2, 3], [4, 5, 6]]})
>>> df.select(pl.col("a").vec.sum())
shape: (1, 1)
┌───────────┐
│ a         │
│ ---       │
│ list[i64] │
╞═══════════╡
│ [5, 7, 9] │
└───────────┘

# alternatively, use functions on column names (with IDE hints and proper type checking):
>>> import polars_vec_ops as vec
>>> df.select(vec.sum("a"))
shape: (1, 1)
┌───────────┐
│ a         │
│ ---       │
│ list[i64] │
╞═══════════╡
│ [5, 7, 9] │
└───────────┘

Operations

All operations work vertically (across rows) on List or Array columns:

• sum() - Sum elements at each position
• mean() / avg() - Calculate mean at each position
• min() / max() - Find min/max at each position
• diff() - Calculate row-to-row differences

Features

• Works with both List and Array dtypes
• Handles null rows and null elements
• Type preservation where possible (Int64, Float64, etc.)
• Fast Rust implementation via PyO3

Development

# Install dev dependencies
uv sync

# Rebuild after modifying Rust code
maturin develop --release

# Run tests
pytest

License

MIT