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A curated list of Polars talks, tools, examples & articles. Contributions welcome !

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Awesome Track Awesome List

A curated list of Polars docs, talks, tools, examples & articles the internet has to offer.

Polars is a lightning-fast DataFrame library for Rust, Python, Node.js and R.
Implemented in Rust, Polars uses Apache Arrow Columnar Format as the memory model.


Contributions of any kind welcome!

Just follow the guidelines by either:

To see the latest entries in the list : click here !

Awesome Polars

Official news

Official documentation

Libraries/Packages/Scripts

Polars plugins

To learn to write, see this great tutorial by @MarcoGorelli!

Python

  • polars for Python - Python polars package to use polars DataFrame from Python.
  • PDS(polars-ds) - A modern take on data science and traditional tabular machine learning with Polars. It provides Python modules that help with EDA tasks for Polars dataframes, machine learning pipelines that are native to Polars (cleaner and faster than Sklearn). In addition, it contains Polars plugin functions that turns many common numerical, statistical functions, least squares, KNN queries, and many other ML metrics into expressions that are executable inside a Polars dataframe.@abstractqqq.
  • tidypolars tidypolars python library built on top of polars library that gives access to methods and functions familiar to R tidyverse users.
  • Working with Polars and XlsxWriter - Guide to using the Python XlsxWriter library with Polars to create Excel reports.
  • Python package seaborn_polars - Python package to plot Polars DataFrames and LazyFrames with seaborn by @pavelcherepan.
  • Python package functime - Machine learning Python package built on Polars for time-series predictions by @neocortexdb. According to the developpers, it's the world's fastest and most feature-full machine learning forecasting library !
  • Ibis Python package for Polars - Ibis is a Python library that provides a lightweight, universal interface for data wrangling. It can be used with Polars.
  • Narwhals - Python files that provides an extremely lightweight compatibility layer between Polars, Pandas, cuDF, and Modin by @narwhals-dev.
  • polars-upgrade - Python package that automatically upgrades your Polars code so it's compatible with future versions by @MarcoGorelli.
  • polars-fuzzy-match - Python package for fuzzy matching with Polars, i.e. matching text elements that are similar but not exactly identical by @bnm3k.
  • Polars for Identifiers and Standard Format Strings - Python package for Processing IBAN, ISINs, URLs and other standard format data in Polars by @abstractqqq.
  • polars_hash - Python package that provides stable hashing functionality across different Polars versions by @ion-elgreco.
  • polars_ta - Python package that provides technical indicator operators rewritten in Polars by @wukan1986.
  • QuickEcharts - Python package for fast and easy echarts with Polars backend by @AdrianAntico.
  • Polars OLS - Python package that provides efficient rust implementations of common linear regression variants and exposes them as simple Polars expressions by @azmyrajab.
  • polars-candle - Python package for for running candle ML models on Polars DataFrames by @wdoppenberg.
  • photoshoot - A pytest plugin library for doing snapshot testing with Polars DataFrames by @ngriffiths13.
  • polar_patch - Python package that brings type safety and type checking for custom Polars plugins by @Summit-Sailors.
  • harley - Polars helper methods to enhance developer productivity by @TomBurdge.
  • cerburus - Python package that prints Polars DataFrames with hierarchical headers by @rhshadrach.

Rust

  • polars for Rust - Rust polars crate to use polars DataFrame with Rust.
  • Polars CLI Polars CLI is a command line interface for running SQL queries with Polars as backend.
  • GeoPolars Geopolars Rust crate that extends the Polars DataFrame library for use with geospatial data.

R

Node.js

Scala/Java

Ruby

Resources

Cheat Sheets

Tutorials & workshops

Blog posts

Talks and videos

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Contributing

Thanks goes to these contributors!