---

Awesome Polars

• Awesome Polars
  • Official news
  • Official documentation
  • Libraries/Packages/Scripts
    • Polars plugins
      • Import / Export
      • Data Manipulation
      • Geographical / Spatial
      • Validation
      • Security / Privacy
      • String parsing
      • Text similarity / Fuzzy Matching
      • Time series / Datetime
      • Machine Learning & Data Science
      • AI
      • Language
      • Finance
      • Networking
      • Mathematical & Statistical Functions
      • General utilities / Performance
      • Statistics / Analytics
      • Visualization
      • Miscellaneous
    • Rust
    • R
    • Go
    • Node.js
    • Scala/Java
    • Ruby
    • .NET
  • Tools Built with Polars
  • Resources
    • Cheat Sheets
    • Books
    • Tutorials & workshops
    • Blog posts
    • Talks and videos
  • Follow
  • Contributing

Official news

• September 2025 : Polars raises €18M Series A to build fast, ergonomic data processing at any scale.
• September 2025 : Polars launches Polars Cloud and a Distributed Engine in Open Beta.
• August 2023 : Polars announces that it has raised a a $4M seed round!
• July 2024 : Python Polars 1.0 release ! See this blog post special announcement.
• September 2024 : Polars has a new lightweight plotting backend.
• September 2024 : GPU acceleration with Polars and NVIDIA RAPIDS.
• February 2025 : Polars Cloud; the distributed Cloud Architecture to run Polars anywhere.

Official documentation

• Documentation - Official user guide for Python, Rust and R.
• Documentation for Python API - Official API Reference for Python.
• Documentation for Rust API - Official API Reference for Rust.
• Documentation for Node.js API - Official API Reference for Node.js.
• Shared library plugins for Polars.
• Documentation for R API - Official API Reference for R.
• Github: Polars Github Organization - Official Polars Github repository.
• Blog posts from Polars - Official blogs posts from Polars.
• Keynote on Polars at EuroSciPy 2023 ⏳ 57 min - Talk by @ritchie46 that dives into Polars and sees what makes it so efficient. It will touch on technologies like Arrow, Rust, parallelism, data structures, query optimization and more.
• Talk about Polars at EuroPython Conference 2023 ⏳ 28 min - Talk by @ritchie46 that introduces Polars and some of its design decisions.

Libraries/Packages/Scripts

Polars plugins

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

You can also try to Polars plugins Cookiecutter by @MarcoGorelli which provides a template to quickly scaffold a Rust-based plugin for the Polars Python library.

Import / Export

• polars_io - Lazily read Stata, SAS, and fixed-width files in Polars by @alipatti.
• polars_readstat - Polars IO plugin to read SAS, Stata and SPSS file by @jrothbaum.
• Working with Polars and XlsxWriter - Guide to using the Python XlsxWriter library with Polars to create Excel reports.
• polars_access_mdbtools - Python package for reading tables from an Access database into Polars dataframes, using mdbtools by @DeflateAwning.
• polars-root - Polars plugin for reading CERN’s ROOT file format by @DanielMaysWilliams.
• polars-fastx - Polars plugin for parsing FASTA and FASTQ files into DataFrames by @apcamargo.
• polars-redis - Polars IO plugin for Redis - scan hashes, JSON, and other data types as LazyFrames with projection pushdown and RediSearch support by @joshrotenberg.
• excelsior - High-performance library for modifying Excel files with Polars.
• polars-mongo - Polars IO plugin that extends polars to read from mongodb collections via the LazyFrame apis by @AThomas314.
• polars-io-tools - Polars plugin extending lazy execution and predicate pushdown across external data sources (SQL, ClickHouse, Datadog, Delta Lake) by @Point72.

Data Manipulation

• tidypolars tidypolars python library built on top of polars library that gives access to methods and functions familiar to R tidyverse users.
• 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.
• pyjanitor - Python package that provides a clean API for cleaning Polars DataFrame @pyjanitor-devs.
• catfact - Python package for working with categorical data in Polars DataFrames by @machow.
• polars-permute-plugin - Polars plugin for easily reordering DataFrame columns by @lmmx.
• polars-schema-index - Polars plugin for flattening nested data by @lmmx.
• polars-expr-hopper - Polars plugin providing a hopper of expressions for automatic, schema-aware application by @lmmx.
• diffly - Python utility for programatically identifying differences between Polars DataFrames including schema differences, row-level mismatches, and column value changes by @Quantco.
• pl-compare - Compare Dataframes to find difference in the schemas, rows and column values by @concur1.
• polarstation - Helper functions to simplify creating and working with Enums by const-ae.
• polynx - Pandas-style query, eval, assign and group-by on string expressions, compiled to native Polars expressions with @var substitution, UDFs and LazyFrame support by @LowellWinston.

Geographical / Spatial

• polars-h3 - Efficient hexagonal indexing for large-scale geospatial analysis by @Filimoa.
• polars-reverse-geocode - This plugin is an offline reverse geocoder for finding the closest city to a given (latitude, longitude) pair by @MarcoGorelli.
• polars-st - Polars plugin that provides geographical/spatial operations on Polars DataFrames, Series, and Expressions by @Oreilles.
• polars-coord-transforms - Polars plugin for coordinates transformation and extractions features by @georgypv.
• PyCanopy - high-performance spatial query layer for Polars, competitive with industry SQL tools in performance

Validation

• polars-validator - Polars plugin that makes Polars DataFrames generics by @baggiponte.
• iban_validation_polars - A package to facilitate validation of IBANs and getting bank identifier and branch identifier as a Polars plugin by @ericqu.
• dataframely - Polars plugin that provides schema and other rule validation for Polars DataFrames by @Quantco.
• daffy - Decorator-first DataFrame contracts/validation (columns/dtypes/constraints) at function boundaries. Supports Polars/Pandas/PyArrow/Modin by @vertti.
• truthound - Enterprise data quality framework with 289 validators, auto-profiling, and zero-configuration schema inference by @seadonggyun4.
• wimsey - Simple and flexible data contracts library, supports profiling and manually specified contracts in json, yaml or python by @benrutter.
• dataprof - Data profiling and quality gates for Polars and pandas DataFrames, CSV, JSON and Parquet, written in Rust, by @AndreaBozzo.

Security / Privacy

• maskops - Native Polars expression plugin for high-speed PII masking and detection, powered by Rust. Supports asterisk masking, HMAC-SHA256 deterministic pseudonymization, and FF3-1 format-preserving encryption. GDPR Art. 4(5)-compliant by @fcarvajalbrown.

String parsing

• polars-url - Polars plugin to parse/extract fields from urls by @condekind.
• polars_iptools - Polars plugin for IP address parsing and enrichment including geolocation by @erichutchins.
• polars-textproc - Polars plugins to apply gopher repetetition penalties and fasttext classifiers to text data by @Apsod.

Text similarity / Fuzzy Matching

• polars-distance - Polars plugin for text similarity/pairwise distance functions by @ion-elgreco.
• 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-strsim - Polars plugin that computes string similarity measures directly on a Polars dataframe by @foxcroftjn.
• polars_sim - Polars plugin that implements fast approximate joins on string columns for polars dataframes by @schemaitat.

Time series / Datetime

• polars-ts - Polars Time Series Extension that offers a wide range of metrics, feature extractors, and various tools for time series forecasting by @drumtorben.
• polars-talib - Polars extension for Ta-Lib - support Ta-Lib functions in Polars expressions by @Yvictor.
• polars-xdt - Polars plugin with extra-datetime-related functionalities by @MarcoGorelli.
• polars-xdt-docs - Polars plugin for business day arithmetic by @MarcoGorelli.
• functime - Machine learning Python package built on Polars for time-series predictions by @functime-org. According to the developpers, it’s the world’s fastest and most feature-full machine learning forecasting library !

Machine Learning & Data Science

• polars-ml - Polars plugin for machine learning by @barak1412.
• polars-candle - Polars plugin for running candle ML models on Polars DataFrames by @wdoppenberg.
• polars-ds - Polars extension for general data science use cases by @abstractqqq.
• polars-fastembed - Polars plugin for embedding DataFrames by @lmmx.
• retrofit - Machine learning framework built with Polars by @AdrianAntico.
• tubular - Scikit-learn pipeline compatible pre-processing steps by @azukds.

AI

• polar_llama - Polars plugin for interacting with LLMs in Polars by @daviddrummond95.
• polars-skills - Official AI agent skills by @polars-inc.
• polars-mcp - A local MCP server for live API lookup against your installed Polars version by @r-brink.

Language

• polar-whichlang - Polars plugin for fast language identification by @rmalouf.
• polars-sbert - Polars plugin for embedding data with Sentence Transformers by @lmmx.

Finance

• polars-trading - A collection of helpful polars plugins and functions for market data processing by @ngriffiths13.
• polars_plugin_option_pricing - Polars plugin exposing rust crate option-pricing by @oscar6echo.
• polars-order-book - Polars plugin for enriching orderbook data with best bid and offer information by @ChristopherRussell.
• polars-fin - Polars plugin to calculate financial metrics by @LVG77.
• polars-bloomberg - Polars plugin that extracts Bloomberg’s financial data directly into polars.DataFrame by @MarekOzana.
• jquantstats - Polars/Narwhals-centric tool for the analysis of financial time series data by @tschm.
• polars-backtest - Polars extension for high-performance portfolio backtesting with Rust, Arrow, T+1 execution, and trade reports by @Yvictor.
• quantwave - Polars-native technical analysis (221 indicators), execution-aware backtesting, and batch/streaming parity with a Rust core and agent skill by @lavs9.

Networking

httpolars - Polars plugin for HTTP operations on columns by @lmmx.

Mathematical & Statistical Functions

• polars_ols - Polars plugin that enables fast linear model Polar expressions by @azmyrajab.
• polars-pairing - Polars plugin that provides pairing functions that encode two natural numbers into a single natural number by @apcamargo.
• polars_rng - Random number generation in Polars via the expression API by @alipatti.
• polars-stats - Polars expression plugin that exposes scipy.stats-style probability distributions by @FBruzzesi.

General utilities / Performance

• polars for Python - Python polars package to use polars DataFrame from Python.
• polars-utils - Collection of utilities for data exploration and analysis with Polars DataFrames by @junghoon-son.
• polars_list_utils - Polars extension that provides a set of utilities for working with List-type columns in Polars DataFrames by @dashdeckers.
• harley - Polars helper methods to enhance developer productivity by @TomBurdge.
• polars-config-meta - Polars plugin for persistent DataFrame-level metadata by @lmmx.
• polars_streaming_csv_decompression Polars IO plugin for reading compressed CSV/TSV files in a streaming fashion by @ghuls.
• life_polars_plugin - Polars plugin to showcase some features of the plugin system by @condekind.
• polars-avro - Polars plugin for reading and writing avro files by @hafaio.
• 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.
• turtle-island - A lightweight utility library for writing Polars Expressions by @jrycw.
• polars-argpartition - Polars plugin that implements the argpartition function by @GiovanniGiacometti.
• polars-path - Polars plugin with filesystem path utilities by @gorkaerana.
• polars-genson - Fast JSON schema inference with support for Polars DataFrames by @lmmx.
• polars-extensions - Polars plugin that extends the capabilities of Polars with functionalities that are not currently found in Polars by @jrasband-dev.
• polars-nexpresso - Polars plugins for generating Polars expressions to work with nested data structures by @heshamdar.
• polarsFE - Polars plugins with helper functions for feature engineering, using Polars by @AdrianAntico.
• polars-row-collector - Facade to collect rows one-by-one into a Polars DataFrame with minimal overhead by @DeflateAwning.
• polars-map - Polars extension that provids a Map extension type and functions by @hafaio.
• polars-telemetry - Python package that profiles Polars queries: per-node timings and row counts, both plans in a browser viewer, findings on what slows a query down, and export to OpenTelemetry or DogStatsD by @jan-krueger.

Statistics / Analytics

• polars_kde - Polars plugin for kernel density estimation by @schemaitat.
• polarscope - Polars plugin for quick data summary, cleaning and visualization of Polars dataframes by @pytoned.

Visualization

• seaborn_polars - Python package to plot Polars DataFrames and LazyFrames with seaborn by @pavelcherepan.
• QuickEcharts - Python package for fast and easy echarts with Polars backend by @AdrianAntico.
• flowview - A visual debugger that shows what happens at each step of your Polars DataFrame transformations in the terminal. By @guillermodotn.
• flexviz - Python library for interactive, cross-filterable charts on 100M+ rows, powered by lazy Polars aggregations and Rust kernels by @jvdd.

Miscellaneous

• polars-finance - A collection of Python Polars plugins and functions for market data processing by @ngriffiths13.
• polars_encryption - Polars plugin that extends Polars with encryption algorithm AES-GSM-SIV by @zlobendog.
• polars-bio - Polars plugin for large-scale genomic analyses which is easy to use and considerably faster and more scalable than existing alternatives by @biodatageeks.
• polars_istr - 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.
• Polars OLS - Python package that provides efficient rust implementations of common linear regression variants and exposes them as simple Polars expressions by @azmyrajab.
• photoshoot - A pytest plugin library for doing snapshot testing with Polars DataFrames by @ngriffiths13.
• cerburus - Python package that prints Polars DataFrames with hierarchical headers by @rhshadrach.
• polars-graphframes - Polars plugin for interconnection of graphs and networks with Frames by @t-ded.
• polars-phonetics - Polars plugin for phonetic algorithms by @LeCodeMinister.
• polars-holidays - Polars plugin for determining if a date is a holiday by @mrjsj.
• polars-cache - Polars plugin to automatically cache the result of expensive queries to disc by @alipatti.
• pl_series_hash - Fast series hashing for polars, useful for caching by @paddymul.
• raffalib-python - STATA-like logging capabilities by @raffaem.
• immunum-polars - high-performance plugin for antibody segmentation and numbering, with up to 1,000,000 antibodies per second on 48-core CPU machine.
• polarise - A Polars-native DataFrame styling tool for HTML visualization by @egayer.

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 pre-alpha Rust crate that extends the Polars DataFrame library for use with geospatial data (not in active development - see top of readme).
• plotlars plotlars is a Rust library designed to facilitate the integration between the Polars data analysis library and Plotly library.
• iban_validation A set of projects to facilitate validation of ibans and getting the bank identifier and branch identifier in Rust, Python and Polars by @ericqu.

R

• rpolars for R - R rpolars package to use polars DataFrame from R.
• tidypolars for R tidypolars package to use polars with tidyverse syntax.
• polarssql - polarssql experimental package which is a DBI-compliant interface to Polars.
• r-polars-dashboard - Dashboard comparing r-polars and py-polars APIs.
• neo-r-polars - Next generation of Polars R API.

Go

• go-polars This project creates Go bindings for Polars.

Node.js

• nodejs-polars for Node.js - Node.js nodejs-polars package to use polars DataFrame from Node.js.

Scala/Java

• scala-polars for Scala and Java - Scala - Java scala-polars is a library for using Polars in Scala and Java projects by @chitralverma.

Ruby

• polars for Ruby - Ruby polars-df gems to use Polars with Ruby.

.NET

• Polars.NET - C# - F# Polars.NET is a library to bring polars to .NET ecosystem, with idiomatic C# Polars.NET and F# Polars.FSharp API nuget packages provided.

Tools Built with Polars

• polars-explorer - A tool that aims to provide a lightweight GUI to data exploration/manipulation tasks using Rust Polars by @brutusyhy.
• polars-mas - A CLI tool and Python library meant to perform large scale multiple association tests, primarily seen in academic research by @idinsmore1.
• octopolars - Pull, filter, and walk a GitHub user’s repositories with Polars by @lmmx.
• table-diff - A tool to generate HTML/Markdown reports highlighting the differences between similar tables by @parker-research.
• polars-query-dev-complexity - A lightweight tool for measuring the authoring complexity of Polars LazyFrame queries by @fran6w.
• Flowfile - A visual ETL tool that builds Polars pipelines on a drag-and-drop canvas or through a Polars-like Python API, with export back to standalone Polars code, by @edwardvaneechoud.
• Ciaren - A local-first visual ETL and ML workflow builder that runs flows on pandas or Polars and exports readable Polars or lazy Polars code, by @ciaren-labs.
• ds-agent-playbook - Autonomous, zero-bloat recipes for Data Science pipelines: automated EDA, deterministic data cleansing, and feature hypothesis synthesis powered by Polars & DuckDB by @udbhav-shrinet.

Resources

Cheat Sheets

• Polars Cheat Sheet - A Polars Cheat Sheet by @FranzDiebold.
• Cheatsheet for Pandas to Polars - A Cheat Sheet that shows how to convert some familiar Pandas commands to Polars by @braaannigan.
• Python Polars: The Definitive Cheatsheet - Quick reference guide for transforming, analyzing, and visualizing data with Python Polars by posit open source.

Books

• Python & Polars: The Definitive Guide - Book on using Python Polars for transforming, summarizing, and visualizing data.
• Polars Cookbook - Practical recipes for transforming and manipulating data with Polars.
• Effective Polars: Optimized Data Manipulation - Book focused on efficient, idiomatic data manipulation with Polars.

Tutorials & workshops

• Modern Polars - A side by side comparison between Polars and Pandas containing code in both frameworks by @kevinheavey.
• A Practical Comparison of Polars and Pandas - A tutorial that showcases several common operations in Pandas and Polars side by side to demonstrate how much easier Polars is by @FlorianWilhelm. There is also an accompanying Jupyter notebook available.
• Prise en main de Polars - A notebook tutorial in French that illustrates the main features of Polars by @romaintailhurat and @linogaliana. There is also an accompanying blog post.
• Running Polars code distributedly - A page that explains how to rung Polars code distributedly with Fugue by @fugue-project.
• • Handling Nested Data in Polars: explode() and unnest() - A comprehensive, 2026-updated guide to flattening complex nested JSON structures and arrays natively in Polars.
• How to display Polars dataframes with itables - A tutorial that explains how to display Polars dataframes with itables by @mwouts.
• Rust Polars: Unlocking High-Performance Data Analysis — Part 1 - First part of an article that explores the world of Rust’s Polars and explain some basic concepts of Polars such as Series by @wiseaidev. Code used is available on Github here.
• Fast String Processing with Polars — Scam Emails Dataset - A tutorial using Polars to implement a text processing pipeline process by @AntonsRuberts. Code used is available on Github here.
• Cookbook Polars for R - A side-by-side comparison of Polars, R base, dplyr and data.table packages by @ddotta.
• Polars Workshop on AWS - A comprehensive workshop comparing Polars to Pandas, exploring a wide range of functions and features by @debnsuma.
• Polars cookbook in Python - This cookbook is a fork of the popular pandas-cookbook and has been modified to use the polars library. By @escobar-west, it uses real-world examples with “all the bugs and weirdness that entails.”
• Data Pipelines with Polars: Step-by-Step Guide - A tutorial that explains how to build data pipelines with Polars by @AntonsRuberts. Code used is available on Github here.
• Python Polars: A Lightning-Fast DataFrame Library - A tutorial that shows how to use Polars with Python ecosystem by @hfhoffman1144. Code used is available on Github here.
• Polars plugins tutorial - How you (yes, you!) can write a Polars Plugin by @MarcoGorelli.
• Scripts and datasets for the O’Reilly book Python Polars: The Definitive Guide - Useful Python notebooks ordered by book chapter by @jeroenjanssens.
• Python-Polars-Tips-and-Tricks - Collection of source code demonstrating tips and tricks in Polars by @StuffbyYuki.
• (Pretty) big data wrangling with DuckDB and Polars - Documentation that introduces the use of DuckDB and Polars with examples in R and Python by @grantmcdermott.
• Introduction course that introduces the concept of DataFrame with Polars and Python. It also proposes some corrected exercices by @TLouf.
• Working With Python Polars - 7-lesson online video course that covers various topics related todata manipulation with Polars by @cltrudeau.
• #100DaysOfPolars articles - List of articles published by @jorammutenge on linkedin #100DaysOfPolars.
• Python Polars Tutorial: A Complete Guide for Beginners - A beginner tutorial to learn how to use Polars in Python by @datacamp.
• A tidyverse user’s guide to Polars - A practical cookbook for R/tidyverse users learning the Polars DataFrame library for Python. Each section pairs Polars syntax with its dplyr/tidyr/lubridate equivalent so the concepts map directly onto what you already know.

Blog posts

• Using the Polars DataFrame Library - A blog post by Wei-Meng Lee to discover the basics of Polars and how it can be used in place of Pandas.
• Why Polars uses less memory than Pandas - A blog post by Itamar Turner-Trauring detailing some techniques to opptimize Pandas memory usage and see how Polars can provide an answer in some cases.
• Plodding with Polars in Python - A blog post by @amitrathore that introduces some basic features of Polars.
• Polars-lazy - A blog post by @ritchie46 and @jorgecarleitao that introduces Polars’ lazy API in Rust.
• Series of posts on Polars - A series of blogpost on Polars usage with a lot of useful tricks and information by @braaannigan. Moreover, Liam also has a Data Analysis with Polars course on Udemy.
• Youtube videos about Polars - A series of short youtube videos about Polars by @braaannigan
• Alternatives to Pandas: Python Polars - An article that explores the Python Polars module as an alternative to Pandas, comparing their similarities and differences and providing some examples by @JohnLockwood
• Pandas vs Polars - A comparison on File I/O - A blog post that evaluates Polars and Pandas in terms of I/O performance and speed when handling large datasets by Wes Poulsen.
• Why is Polars All The Rage? - An article that explains why Polars will become very popular by SeattleDataGuy and Daniel Beach.
• Polars vs Pandas — 4 key concept differences - An article that helps to understand key differences between Pandas and Polars Data Science libraries by @DataScienceDisciple.
• Replacing Pandas with Polars. A Practical Guide - A blog post comparing some common functions between Pandas and Polars by @danielbeach. Code used is available on Github here.
• Dataframe Showdown – Polars vs Spark vs Pandas vs DataFusion. Guess who wins? - A short article that presents a performance test between Polars, Pandas, Datafusion and Spark on a csv dataset by @danielbeach. Code used is available on Github here.
• 7 Easy Steps To Switch From Pandas to Lightning Fast Polars And Never Return - A cheat sheet blog post of the most common Pandas operations translated into Polars by BexTuychiev.
• Polars for initial data analysis, Polars for production - A blog post that shows how to use Polars for initial data analysis and then effectively in production by @itamarst.
• DuckDB vs Polars vs Spark! - An article that performs a benchmark against duckdb/Polars/spark, with varying row count, with swap usage as another metric, in addition to runtime in seconds. Code used is available on Github here.
• Benchmarking PySpark Pandas, Pandas UDFs, and Fugue Polars - A blog post that compares the execution time of fugue + Polars, Pandas UDFs and PySpark Pandas by @kvnkho.
• Pandas vs. Polars: The Battle of Performance - An another blog post that compares the performance between Pandas and Polars across a range of common data manipulation tasks by @makeuseofcode. Code used is available on Github.
• Pandas 2.0 vs Polars: The Ultimate Battle - A blog post that analyzes in terms of Syntax, Speed, and Usability between Pandas 2.0 and Polars 0.17.0 by @priyanshu7401.
• Polars - modern data frame library - A blog post that describes why Polars could be a better alternative to pandas, dplyr or data.table by @DSkrzypiec.
• The fastest way to read a CSV file in Python - A blog post that compares different ways (including Polars, pyarrow and C) to read a CSV file with Python by Finn Andersen.
• Polars in the aRtic! - An another blog post that compares the performance between Pandas and Polars across a range of common data manipulation tasks by @MCodrescu. Code used is available on Github.
• A Polars exploration into Kedro - A blog post that explains how Polars can be used instead of pandas in Kedro for your data catalog and data manipulation by @astrojuanlu.
• High Performance Data Manipulation in Python: pandas 2.0 vs. polars - A blog post that compares differences between Python pandas 2.0 and Polars libraries by @jcanalesluna.
• Lightning-fast queries with Polars - Another blog post that is a good introduction to Polars by @astrojuanlu.
• Polars – Laziness and SQL Context. - A blog post that presents two good reasons to adopt Polars : Lazy and SQL Context by @danielbeach.
• Exploring Polars - The Lightning-Fast DataFrame Library in Python - A blog post on the basics of Polars by @mddas.
• Pandas vs Polars – Speed Comparison - A blog post that compares the performance of Polars, Pandas and Pandas 2.0 by @StuffbyYuki. Code used is available on Github here.
• LazyFrame vs DataFrame in Polars – Performance Comparison - A blog post that introduces what LazyFrame is in Polars and its performance gain compared to DataFrame by @StuffbyYuki. Code used is available on Github here.
• Querying Polars DataFrames using SQL - A blog post that shows how to use the SQLContext object in Python to query a Polars DataFrame directly using SQL by @weimenglee.
• Polars vs Pandas: A Brief Tale of Two DataFrame Libraries - A blog post that compares Polars and Pandas focusing in particular on optional dependencies by @ranggakd.
• EDA with Polars: Step-by-Step Guide for Pandas Users (Part 1) - A blog post that describes the main data processing operations with Polars in Python by @AntonsRuberts. Code used is available in this notebook.
• EDA with Polars: Step-by-Step Guide to Aggregate and Analytic Functions (Part 2) - A blog post that shows how to perform with Polars and Python some fairly complex aggregates, rolling statistics and more by @AntonsRuberts. Code used is available in this notebook.
• Pyspark or Polars — What should you use? - A blog post that explores and breaks down some of the similarities between PySpark and Polars. It provides insights on when to choose one over the other.
• Getting Started with the Polars Data Manipulation Library - A blog post that presents some simple features of Polars using Python by Juveriya Mahreen.
• 8 ways pandas really losing to Polars for quick market data analysis - A newsletter that compares the performance of Polars to Pandas for many common data manipulation techniques by PyQuant News.
• All that Polars that Make You Forget Pandas - A blog post that explores some deeper reasons behind the performance gains of Polars over Pandas.
• Polars vs Pandas. Inside an AWS Lambda - A blog post that covers the topic of using Polars vs Pandas inside an AWS Lambda to do data processing by @danielbeach. Code used is available on Github here.
• DuckDB vs Polars for Data Engineering - A blog post that compares Polars and DuckDB with pipelines for Data Engineering by @danielbeach.
• Pandas vs Polars: A database speed test. Who wins? - A blog post that compares the run-time of reading a database into a dataframe using Pandas versus using Polars by Thomas Reid.
• Polars and Pandas : What’s the difference ? - A blog post that explains how Polars works under the hood and th best use cases for Polars and Pandas by @t-redactyl.
• Understanding the Polars nested column types - A blog post that helps to understand how nested column types works in Polars by @braaannigan.
• Polars vs DuckDB for Delta Lake ops - A blog post that compares Polars to DuckDB using Delta Lake by @wolliq.
• Enhancing Data Analytics with Polars and MinIO - A blog post that explains how to use Polars with Minio’s open-source object storage by @IndexSeek.
• Partitioning Polars DataFrame on S3 with Apache Arrow - A blog post that explains how to partition large Polars DataFrames in AWS S3 by Matteo Arellano.
• Goodbye Spark. Hello Polars + Delta Lake - An article that presents how to use Polars in addition to Delta Lake by @danielbeach.
• How to learn Polars with ChatGPT? - An article that explains how to learn fundamental Polars concepts with ChatGPT by Suhith Illesinghe.
• Date and DateTime Manipulation in Polars - A blog post that shows examples of doing a number of date and datetime manipulations in Polars (Python) by @danielbeach. Code used is available on Github here.
• Pandas2 and Polars for Feature Engineering - A blog post that compares Pandas2 and Polars for Feature Engineering tasks with Python by @hopswork.
• Spark vs Polars. Real-life Test Case - A blog post in which the author tests whether Polars is able to handle “real amounts of data” and “really replace some production Spark workloads.” by @danielbeach. Code used is available on Github here.
• Using Polars Plugins for a 14x Speed Boost with Rust - A blog post thats shows the use of Polars plugin system for Rust from some concrete examples by @ngriffiths13.
• Working with DateTime data in Polars - A blog post to helps you with the main operations that can be done with datetime data by Rielly Griffiths.
• Revolutionize Your Data Analysis: Polars Outperforms Pandas by Up to 5x in Numerical Filter Operations! - A blog post that compares Polars with Pandas by examining their performance in the real world by Daniel Builescu.
• Time series Analysis with Polars - A short blog post that explains how to deal with temporal datasets by @gaborschulz. Full helpful notebook available here.
• Interesting thread about Polars on Hacker News
• Level Up Your Data Analysis with Polars: A Powerful DataFrame Library for Speed and Efficiency - A blog post that describes the main features of Polars (with benchmarks) by ravi-m.
• polars’ Rgonomic Patterns - A blog post that deeps dive into some of the advanced data wrangling functionality in python’s Polars package by @emilyriederer.
• Great Tables: The Polars DataFrame Styler of Your Dreams - A post that shows how Great Tables package uses polars expressions to make delightful tables by @machow.
• Polars dataframe’s plugins and extensibility: getting started - A post that illustrates the possibility of extending the core Dataframe API of Polars with a few examples by @brunocous.
• 15 Pandas ↔ Polars ↔ SQL ↔ PySpark Translations - A post that depicts the 15 most common tabular operations in Polars and their corresponding translations in Pandas, SQL and PySpark by @ChawlaAvi.
• LazyFrame: Exploring Laziness in Dataframes from Polars in Python - A blog post that introduces LazyFrames with Polars an Python by Manoj Das.
• Data Statistics in Polars - A post that explains how to extract insightful information from your data in Polars by Alexandre Petit.
• Groupby in Polars - A post that explains how to Learn how to do group data using Polars by Alexandre Petit.
• DuckDB vs Polars - Thunderdome. - A blog post that compares Polars and DuckDB with the use of 16 GB of data on a machine of only 4 GB by @danielbeach.
• How moving from Pandas to Polars made me write better code without writing better code - A post that describs the process of “Polarification” of code written with Pandas by @duvenagep.
• Revisiting a Classic Cheminformatics Paper with Polars: The Wiener Index - A science blog post that uses Polars to track the information for the molecules in DataFrames by @bertiewooster.
• How to start using Polars & DuckDB together for data analysis - A post that demonstrates the usage of Polars with DuckDB to perform similar data transformations as is done using Pandas by @sumaniitm.
• Anatomy of a Polars Query: A Syntax Comparison of Polars vs SQL - A post that compares Polars syntax to SQL by @bfeif.
• Pandas vs. Polars — Time to Switch? - A blog post that compares Polars to Pandas in a series of 4 benchmarks performed on a csv file with 11 million rows by @daradecic.
• How to JOIN datasets in Polars … compared to Pandas - A blog post compares dataframe joins in Polars vs Pandas by @danielbeach.
• DuckDB vs Polars - Which One Is Faster? - An unofficial benchmark on DuckDB and Polars by @StuffbyYuki.
• Pandas vs Polars? Bid Adieu to Pandas and Switch To Polars! - An article that compares Polars to Pandas with a dataset of 1.2 GB. Code used is available on Github here.
• Polars vs. Pandas: 30 Comparison Functions - A reminder blog post that compares 30 functions written with Polars and Pandas by Yunuskaradagg.
• Polars vs. SQL: When to Choose Python for Your Data Adventures - A blog post that explores some common functions and their counterparts in both Polars and SQL by Yunuskaradagg.
• Age of DataFrames II: Polars Edition - A blog post that illustrates the features of Polars through the analysis of a tournament from the video game Age of Empires II by [@woutergins]. Source code available here
• Polars: A Modern DataFrame Library - An article that introduces to Polars design and its main features by @gox6.
• Mastering Polars: High-Efficiency Data Analysis and Manipulation - An article that provides a comprehensive introduction of Polars, highlighting its features and showcasing practical examples to get started.
• Encrypting data with Polars - A post that illustrates how to use the polars_encryption plugin to encrypt data with Polars by @zlobendog.
• Case Study Comparing Pandas and Polars with 1 Million Rows Data - An blog post that compares benchmarking scores with the Independent samples t-test and Welch’s t-test using Python.
• How to Move From Pandas to Polars - A blog post that explains how to move from Pandas to Polars using Pycharm by [@Cheukting].
• DuckDB vs Polars — Which One Is Faster? - An unofficial benchmark on DuckDB and Polars by Yuki Kakegawa.
• Polars: The Must-Know Data Frame Library Every Data Scientist Should Know - A blog post that provides a good first guide to the features of Polars by @AnsaBaby.
• Benchmarking energy usage and performance of Polars and pandas - A blog post by the Polars team itself benchmarking Polars and Pandas.
• Why I’m Switching to Polars - A blog post that explains the reasons why Ari Lamstein now uses Polars by @arilamstein.
• Polars: A Modern DataFrame Library for High-Performance Data Analysis in Python - An article that presents data manipulation operations focusing on eager execution by Ardi Arunaditya.
• Using Polars in Rust for high-performance data analysis - An article that looks how to use Polars to build a basic data analysis application, which exposes data sets and querying capabilities via a REST-based Web API by @Mario Zupan.
• Pandas vs Polars: Performance Benchmarks for Common Data Operations - A blog post that compares performance on common data operations between Polars and Pandas by Vinod Chugani.
• The Polars vs pandas Difference Nobody is Talking About - A blog post that talks about non-elementary group-by aggregations with Polars by @marcogorelli.
• Translating Pandas to Polars - A blog post that that proposes 20 code translations from Pandas to Polars by @Rohit-Salunke.
• Tutorials about Polars - A list of blog posts on Polars topics by @sparkbyexamples.
• How to Deal With Missing Data in Polars - A post that covers practical techniques for managing missing data with Polars by Ian Eyre.
• Polars intro A short demo that introduces the Polars dataframe library through a marimo notebook by @rparkr.
• Build a Decision Tree in Polars from Scratch - A post that explains how to build a decision tree with Polars by @tocab. Code used is available on Github here.
• Pandas vs Polars: is it time to change? - A post that summarizes the main issues involved in the transition from Pandas to Polars by Michelangelo Florio.
• The Complete Guide to Polars for Data Science - A hands-on tutorial that teaches how to load, manipulate, transform and optimize data sets with Polars in Python by @norochalise. Code used is available on Github here.
• Pandas vs Polars : Comparaison des performances et de la mémoire - A 2025 benchmark that compares the performance of Polars and Pandas by @moncoachdata. Code used is available on Github here.
• Polars for Pandas Users — A Blazing Fast DataFrame Alternative — A tutorial article that shows how to migrate from Pandas to Polars with code examples and performance optimization tips by Vinod Chugani.
• Data Validation Libraries for Polars (2025 Edition) - A survey of five Python data validation libraries compatible with Polars, highlighting their strengths and trade-offs for robust data pipeline validation in 2025 by @rich-iannone.
• Reshape Data in Polars Efficiently from Wide to Long Form - A blog post list that details efficient transformation for Polars DataFrames from wide to long form by @samukweku.
• Polars Boosted My Algorithm’s Speed by 25x - A blog post that explains how using Polars increases code execution speed by 25 times compared to Pandas by @hatdropper1977.
• DuckDB vs Polars. Wait. DuckDB and Polars - A blog post that helps you choose between Polars and DuckDB based on use cases by @danielbeach.
• Pandas vs Polars in 2025 — Should You Finally Make the Switch? - An article that compares performance and features between Polars and Pandas in 2025 by @Gecofer.
• How to Use the Polars Library in Python for Data Analysis - An end 2025 beginner-friendly introduction to the Polars library in Python by Sara Jadhav.
• Polars vs pandas: Choosing the Right Python DataFrame Library for Your Data Workflow -A Databricks article comparing Pandas and Polars across performance, syntax, features, and use cases for Python data analysis by @databricks.

Talks and videos

• Polars: Blazingly Fast DataFrames in Rust and Python ⏳ 37 min - Introduction to Polars by databricks.
• Polars: The Next Big Python Data Science Library… written in Rust? ⏳ 14 min - A short video tutorial to get started coding with Polars by @RobMulla.
• The Best library for building Data Pipelines… ⏳ 12 min - A video that compares Pandas, Spark and Polars for working with data in Python by @RobMulla.
• Expressive & fast dataframes in Python with polars ⏳ 28 min - A video that reviews some alternatives to Pandas for Python and then demonstrates some Polars features by Juan Luis Cano Rodríguez.
• Polars Introduction for Python with a 128GB Ryzen 24-core Benchmark vs Pandas ⏳ 12 min - A video that provides an introduction to Polars for Python by @jeffheaton. Notebook used for the video in this github repo.
• Polars: The main alternative to pandas in Python!? ⏳ 57 min - A Polars tutorial series on Youtube by @martinbel. Notebooks and datasets used for the videos available in this github repo.
• Polars vs Pandas ⏳ 37 min - A detailed video on Youtube that compares Polars and Pandas by @hu-po.
• Polars: The Super Fast Dataframe Library for Python — Goodbye Pandas? - An article and a video ⏳ 19 min that explores some basic features of Polars by Frank Andrade.
• Manipulación de Datos con Polars en python ⏳ 51 min - A detailed tutorial video in Spanish that shows 20 Polars functions to perform 80% of the tasks of a data scientist.
• An opinionated introduction to Polars - Great Polars introduction slides from @krlng at PyCon 2023.
• Polars - make the switch to lightning-fast dataframes ⏳ 30 min - A talk that reports an experience switching from Pandas to Polars in a real-world ML project by @datenzauberai. Slides are available here.
• Polars vs Pandas | detailed test with explained results ⏳ 22 min - A video that presents 8 distinct tests which demonstrates differences between Pandas and Polars by @vb100. Associated github repo is here.
• How to update mass data using Polars DataFrame ⏳ 9 min - A video that presents the process of writing code to update mass columns across CSV or data files by @AmitXShukla. Notebook used for the video in this github repo.
• Using the Rust Polars DataFrame library in a CLI ⏳ 4 min - A video that shows how to integrate Polars in a commande line interface by @paiml.
• The Ultimate Guide to Data Wrangling with Python | Rust Polars Data Frame ⏳ 10 videos - A playlist of 10 videos (WIP) that equips you with all the necessary knowledge required to utilize Python Polars Data Frame by @AmitXShukla.
• Polars DataFrame ⏳ 41 min - A video that shows some basic manipulations with Polars and Python by @vedica1011. Notebook used for the video in this github repo.
• Why I switched grom Pandas to Polars ⏳ 53 min - A workshop that breaks down the 3 reasons why you could switched from Pandas to Polars by @bfeif. Notebook used for the video in this github repo.
• Intro to Polars ⏳ 7 videos - A playlist of 7 videos that introduces the basic concepts of Polars (DataFrames, filtering, splitting…) by Joram Mutenge.
• Machine Learning with Polars ⏳ 6 videos - A playlist of 6 videos that analyzing and cleaning data using Polars to train machine learning models by Joram Mutenge.
• Pandas and Polars with Marco Gorelli ⏳ 55 min - A podcast by The Developers’ Bakery that compares the performance of Polars to Pandas by @MarcoGorelli.
• Library of the week 13 : Polars with Python ⏳ 15 min - A video that presents Polars with Python by @enarroied. Article supplied with the video in this page.
• Polars is the Pandas killer | PyData Tel Aviv 2024 ⏳ 22 min - A video that shows how Polars is competing head to head with scale, speed and ease of use for dataframe solution in python by Igor Mintz.
• Polars-Cookbook in Python - Polars cookbook with organized by Python notebooks and chapter by @StuffbyYuki.
• Polars - An Optimized Dataframe Library ⏳ 84 min - A video that compares the main features of Polars with those of Pandas, with a focus on speeding up your data pipeline by @mattharrison.
• DataFrames on steroids with Polars ⏳ 42 min - A video that demonstrates Polars for Python and shows how much faster it is compared to pandas while remaining just as convenient by @prosoitos. Slides are available here.
• Pandas, Polars and the DataDrame Consortium ⏳ 25 min - A video that offers a detailed performance comparison between Polars and Pandas. This analysis serves as a foundation for the introduction of the DataFrame Consortium, which aims to standardize data manipulation libraries.
• Integrate Polars DataFrame with Ollama ⏳ 12 min - A video that demonstrates how to integrate Polars with Ollama local models to do data analysis by @fahdmirza.
• Polars basics playlist - A playlist that introduces the basic features of Polars in an instructive way.
• Polars - SQL Interface for Querying DataFrames ⏳ 20 min - A video that shows how to use SQL to query the data in Polars DataFrames by @bugbytes-io.
• How to Learn the Polars DataFrame Library ⏳ 110 min - A long video that explains and illustrates the basic principles of Polars by @KeithGalli. Associated github repo is here.
• Polars with Plotly ⏳ 19 min - A video that shows the usage of Polars with the Plotly graphic library by Plotly. <>
• Polars and time series | PyData 2024 ⏳ 29 min - A video that shows how to use Polars effectively for time series analysis iby @MarcoGorelli.
• How to Learn the Polars DataFrame Library ⏳ 65 min - A video that enables to learn practical techniques for data manipulation and advanced transformations by @kimfetti. Associated github repo is here.
• Polars: Past, Present and Future with Ritchie Vink ⏳ 71 min - A video in which Jon Krohn talks with the creator of Polars, Ritchie Vink (@ritchie46), about why Polars is important, how it works, and where it’s going by @jonkrohn.
• Understanding Polars Expressions when you’re used to Pandas ⏳ 36 min - A video that explains how to understand expressions from a Pandas perspective by @marcogorelli.
• Understanding Polars Expressions when you’re used to Pandas ⏳ 31 min - A video that explains how to write your own Polars Plugin by @marcogorelli.
• Polars - Talk Python To Me Ep.402 ⏳ 69 min - A video in which Ritchie Vink gives a look at Polars by Talk Python To Me.
• 10 Polars Tools and Techniques To Level Up Your Data Science - Talk Python To Me Ep.510 ⏳ 58 min - A video in which Christopher Trudeau shares his recent work with Polars and highlights a collection of complementary Polars extensions and libraries by Talk Python To Me.

Follow

• pola-rs (@pola-rs) - Github organisation for Polars
• Ritchie Vink (@ritchie46) - Author of Polars
• Stijn de Gooijer (@stinodego) - Member of Polars organisation
• Alexander Beedie (@alexander-beedie) - Contributor to Polars projects
• Marco Edward Gorelli (@MarcoGorelli) - Contributor to Polars projects
• Eitsupi (@eitsupi) - Contributor to R Polars project
• Etienne Bacher (@etiennebacher) - Contributor to R Polars project
• PolarsCodeAcademy - Youtube Channel with thematic videos about Polars

Contributing

• Damien Dotta (@ddotta) - Maintainer of Awesome Polars list

Thanks goes to these contributors!