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awesome-polars

A curated list of Polars talks, tools, examples & articles. Contributions welcome !
https://github.com/ddotta/awesome-polars

Last synced: 11 days ago
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  • Contributing

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    • .NET

      • Polars.NET - [C#](https://learn.microsoft.com/en-us/dotnet/csharp/) - [F#](https://learn.microsoft.com/en-us/dotnet/fsharp/) `Polars.NET` is a library to bring polars to .NET ecosystem, with idiomatic C# [Polars.NET](https://www.nuget.org/packages/Polars.NET) and F# [Polars.FSharp](https://www.nuget.org/packages/Polars.FSharp) API nuget packages provided.

    • Node.js

      • nodejs-polars for Node.js - [Node.js](https://nodejs.org/en/) `nodejs-polars` package to use polars DataFrame from Node.js.

    • Polars plugins

      • tidypolars
      • Working with Polars and XlsxWriter - Guide to using the Python [XlsxWriter](https://xlsxwriter.readthedocs.io/index.html) library with Polars to create Excel reports.
      • functime - Machine learning Python package built on Polars for time-series predictions by [@neocortexdb](https://github.com/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](https://github.com/ibis-project/ibis) is a Python library that provides a lightweight, universal interface for data wrangling. It can be used with Polars.
      • polars-ml - Polars plugin for machine learning by [@barak1412](https://github.com/barak1412).
      • seaborn_polars - Python package to plot Polars DataFrames and LazyFrames with [seaborn](https://seaborn.pydata.org/) by [@pavelcherepan](https://github.com/pavelcherepan).
      • polars-xdt - Polars plugin with extra-datetime-related functionalities by [@MarcoGorelli](https://github.com/MarcoGorelli).
      • polars-ds - Polars extension for general data science use cases by [@abstractqqq](https://github.com/abstractqqq).
      • polars-upgrade - Python package that automatically upgrades your Polars code so it's compatible with future versions by [@MarcoGorelli](https://github.com/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](https://github.com/bnm3k).
      • polars_istr - Python package for Processing IBAN, ISINs, URLs and other standard format data in Polars by [@abstractqqq](https://github.com/abstractqqq).
      • polars_hash - Python package that provides stable hashing functionality across different Polars versions by [@ion-elgreco](https://github.com/ion-elgreco).
      • polars_ta - Python package that provides technical indicator operators rewritten in Polars by [@wukan1986](https://github.com/wukan1986).
      • QuickEcharts - Python package for fast and easy echarts with Polars backend by [@AdrianAntico](https://github.com/AdrianAntico).
      • Polars OLS - Python package that provides efficient rust implementations of common linear regression variants and exposes them as simple Polars expressions by [@azmyrajab](https://github.com/azmyrajab).
      • polars-trading - A collection of helpful polars plugins and functions for market data processing by [@ngriffiths13](https://github.com/ngriffiths13).
      • polars-candle - Polars plugin for running [candle](https://github.com/huggingface/candle) ML models on Polars DataFrames by [@wdoppenberg](https://github.com/wdoppenberg).
      • polars_encryption - Polars plugin that extends Polars with encryption algorithm AES-GSM-SIV by [@zlobendog](https://github.com/zlobendog).
      • polars_iptools - Polars plugin for IP address parsing and enrichment including geolocation by [@erichutchins](https://github.com/erichutchins).
      • life_polars_plugin - Polars plugin to showcase some features of the plugin system by [@condekind](https://github.com/condekind).
      • polars-url - Polars plugin to parse/extract fields from urls by [@condekind](https://github.com/condekind).
      • this great tutorial
      • polars-distance - Polars plugin for text similarity/pairwise distance functions by [@ion-elgreco](https://github.com/ion-elgreco).
      • polars-reverse-geocode - This plugin is an offline reverse geocoder for finding the closest city to a given (latitude, longitude) pair by [@MarcoGorelli](https://github.com/MarcoGorelli).
      • Narwhals - Python files that provides an extremely lightweight compatibility layer between Polars, Pandas, cuDF, and Modin by [@narwhals-dev](https://github.com/narwhals-dev).
      • photoshoot - A pytest plugin library for doing snapshot testing with Polars DataFrames by [@ngriffiths13](https://github.com/ngriffiths13).
      • polar_patch - Python package that brings type safety and type checking for custom Polars plugins by [@Summit-Sailors](https://github.com/Summit-Sailors).
      • harley - Polars helper methods to enhance developer productivity by [@TomBurdge](https://github.com/TomBurdge).
      • polars_sim - Polars plugin that implements fast approximate joins on string columns for polars dataframes by [@schemaitat](https://github.com/schemaitat).
      • polars-strsim - Polars plugin that computes string similarity measures directly on a Polars dataframe by [@foxcroftjn](https://github.com/foxcroftjn).
      • cerburus - Python package that prints Polars DataFrames with hierarchical headers by [@rhshadrach](https://github.com/rhshadrach).
      • polars-validator - Polars plugin that makes Polars DataFrames generics by [@baggiponte](https://github.com/baggiponte).
      • polars-h3 - Efficient hexagonal indexing for large-scale geospatial analysis by [@Filimoa](https://github.com/Filimoa).
      • polars-utils - Collection of utilities for data exploration and analysis with Polars DataFrames by [@junghoon-son](https://github.com/junghoon-son).
      • polars-st - Polars plugin that provides geographical/spatial operations on Polars DataFrames, Series, and Expressions by [@Oreilles](https://github.com/Oreilles).
      • polars-pairing - Polars plugin that provides pairing functions that encode two natural numbers into a single natural number by [@apcamargo](https://github.com/apcamargo).
      • polars-bio - Polars plugin for large-scale genomic analyses which is easy to use and considerable faster and more scalabe than existing alternatives by [@biodatageeks](https://github.com/biodatageeks).
      • polars-ts - Polars Time Series Extension that offers a wide range of metrics, feature extractors, and various tools for time series forecasting by [@drumtorben](https://github.com/drumtorben).
      • polars-config-meta - Polars plugin for persistent DataFrame-level metadata by [@lmmx](https://github.com/lmmx).
      • polars-talib - Polars extension for Ta-Lib - support Ta-Lib functions in Polars expressions by [@Yvictor](https://github.com/Yvictor).
      • polars_access_mdbtools - Python package for reading tables from an Access database into Polars dataframes, using mdbtools by [@DeflateAwning](https://github.com/DeflateAwning).
      • polars_list_utils - Polars extension that provides a set of utilities for working with List-type columns in Polars DataFrames by [@dashdeckers](https://github.com/dashdeckers).
      • iban_validation_polars - A package to facilitate validation of IBANs and getting bank identifier and branch identifier as a Polars plugin by [@ericqu](https://github.com/ericqu).
      • polars_streaming_csv_decompression
      • polars for Python - [Python](https://www.python.org/) `polars` package to use polars DataFrame from Python.
      • dataframely - Polars plugin that provides schema and other rule validation for Polars DataFrames by [@Quantco](https://github.com/Quantco).
      • polar_llama - Polars plugin for interacting with LLMs in Polars by [@daviddrummond95](https://github.com/daviddrummond95).
      • polar-whichlang - Polars plugin for fast language identification by [@rmalouf](https://github.com/rmalouf).
      • polars-avro - Polars plugin for reading and writing avro files by [@hafaio](https://github.com/hafaio).
      • pyjanitor - Python package that provides a clean API for cleaning Polars DataFrame [@pyjanitor-devs](https://github.com/pyjanitor-devs).
      • turtle-island - A lightweight utility library for writing Polars Expressions by [@jrycw](https://github.com/jrycw).
      • catfact - Python package for working with categorical data in Polars DataFrames by [@machow](https://github.com/machow).
      • Polars plugins Cookiecutter - based plugin for the Polars Python library.
      • polars_io - Lazily read Stata, SAS, and fixed-width files in Polars by [@alipatti](https://github.com/alipatti).
      • polars_readstat - Polars IO plugin to read SAS, Stata and SPSS file by [@jrothbaum](https://github.com/jrothbaum).
      • polars-root - Polars plugin for reading CERN's ROOT file format by [@DanielMaysWilliams](https://github.com/DanielMaysWilliams).
      • polars-permute-plugin - Polars plugin for easily reordering DataFrame columns by [@lmmx](https://github.com/lmmx).
      • polars-schema-index - Polars plugin for flattening nested data by [@lmmx](https://github.com/lmmx).
      • polars-expr-hopper - Polars plugin providing a hopper of expressions for automatic, schema-aware application by [@lmmx](https://github.com/lmmx).
      • polars-coord-transforms - Polars plugin for coordinates transformation and extractions features by [@georgypv](https://github.com/georgypv).
      • polars-textproc - Polars plugins to apply gopher repetetition penalties and fasttext classifiers to text data by [@Apsod](https://github.com/Apsod).
      • polars-xdt-docs - Polars plugin for business day arithmetic by [@MarcoGorelli](https://github.com/MarcoGorelli).
      • polars-fastembed - Polars plugin for embedding DataFrames by [@lmmx](https://github.com/lmmx).
      • polars-sbert - Polars plugin for embedding data with Sentence Transformers by [@lmmx](https://github.com/lmmx).
      • polars_plugin_option_pricing - Polars plugin exposing rust crate option-pricing by [@oscar6echo](https://github.com/oscar6echo).
      • polars-order-book - Polars plugin for enriching orderbook data with best bid and offer information by [@ChristopherRussell](https://github.com/ChristopherRussell).
      • polars-fin - Polars plugin to calculate financial metrics by [@LVG77](https://github.com/LVG77).
      • httpolars - Polars plugin for HTTP operations on columns by [@lmmx](https://github.com/lmmx).
      • polars_rng - Random number generation in Polars via the expression API by [@alipatti](https://github.com/alipatti).
      • polars-argpartition - Polars plugin that implements the argpartition function by [@GiovanniGiacometti](https://github.com/GiovanniGiacometti).
      • polars-path - Polars plugin with filesystem path utilities by [@gorkaerana](https://github.com/gorkaerana).
      • polars_kde - Polars plugin for kernel density estimation by [@schemaitat](https://github.com/schemaitat).
      • polars-graphframes - Polars plugin for interconnection of graphs and networks with Frames by [@t-ded](https://github.com/t-ded).
      • polars-phonetics - Polars plugin for phonetic algorithms by [@LeCodeMinister](https://github.com/LeCodeMinister).
      • polars-holidays - Polars plugin for determining if a date is a holiday by [@mrjsj](https://github.com/mrjsj).
      • polars-fastx - Polars plugin for parsing FASTA and FASTQ files into DataFrames by [@apcamargo](https://github.com/apcamargo).
      • polars-cache - Polars plugin to automatically cache the result of expensive queries to disc by [@alipatti](https://github.com/alipatti).
      • polars-genson - Fast JSON schema inference with support for Polars DataFrames by [@lmmx](https://github.com/lmmx).
      • polars-finance - A collection of Python Polars plugins and functions for market data processing by [@ngriffiths13](https://github.com/ngriffiths13).
      • pl_series_hash - Fast series hashing for polars, useful for caching by [@paddymul](https://github.com/paddymul).
      • polars-extensions - Polars plugin that extends the capabilities of Polars with functionalities that are not currently found in Polars by [@jrasband-dev](https://github.com/jrasband-dev).
      • polars-nexpresso - Polars plugins for generating Polars expressions to work with nested data structures by [@heshamdar](https://github.com/heshamdar).
      • retrofit - Machine learning framework built with Polars by [@AdrianAntico](https://github.com/AdrianAntico).
      • polarsFE - Polars plugins with helper functions for feature engineering, using Polars by [@AdrianAntico](https://github.com/AdrianAntico).
      • polars-bio - [Polars plugin](https://github.com/biodatageeks/polars-bio) for large-scale genomic analyses which is easy to use and considerably faster and more scalable than existing alternatives by [@biodatageeks](https://github.com/biodatageeks).
      • polars-bloomberg - Polars plugin that extracts Bloomberg’s financial data directly into polars.DataFrame by [@MarekOzana](https://github.com/MarekOzana).
      • polars-bio - [Polars plugin](https://github.com/biodatageeks/polars-bio) for large-scale genomic analyses which is easy to use and considerably faster and more scalable than existing alternatives by [@biodatageeks](https://github.com/biodatageeks).
      • polars-redis - Polars IO plugin for Redis - scan hashes, JSON, and other data types as LazyFrames with projection pushdown and RediSearch support by [@joshrotenberg](https://github.com/joshrotenberg).
      • excelsior - High-performance library for modifying Excel files with Polars.
      • daffy - Decorator-first DataFrame contracts/validation (columns/dtypes/constraints) at function boundaries. Supports Polars/Pandas/PyArrow/Modin by [@vertti](https://github.com/vertti).
      • truthound - Enterprise data quality framework with 289 validators, auto-profiling, and zero-configuration schema inference by [@seadonggyun4](https://github.com/seadonggyun4).
      • polars-row-collector - Facade to collect rows one-by-one into a Polars DataFrame with minimal overhead by [@DeflateAwning](https://github.com/DeflateAwning).
      • wimsey - Simple and flexible data contracts library, supports profiling and manually specified contracts in json, yaml or python by [@benrutter](https://github.com/benrutter).
      • tubular - Scikit-learn pipeline compatible pre-processing steps by [@azukds](https://github.com/azukds).
      • diffly - Python utility for programatically identifying differences between Polars DataFrames including schema differences, row-level mismatches, and column value changes by [@Quantco](https://github.com/Quantco).
      • raffalib-python - [STATA](https://www.stata.com/)-like logging capabilities by [@raffaem](https://github.com/raffaem).
      • polars-mongo - Polars IO plugin that extends polars to read from mongodb collections via the LazyFrame apis by [@AThomas314](https://github.com/AThomas314).
      • pl-compare - Compare Dataframes to find difference in the schemas, rows and column values by [@concur1](https://codeberg.org/concur1).
      • functime - Machine learning Python package built on Polars for time-series predictions by [@functime-org](https://github.com/functime-org). According to the developpers, it's the world's fastest and most feature-full machine learning forecasting library !
      • jquantstats - Polars/Narwhals-centric tool for the analysis of financial time series data by [@tschm](https://github.com/tschm).
      • polars-map - Polars extension that provids a Map extension type and functions by [@hafaio](https://github.com/hafaio).
      • polars_kde - Polars plugin for kernel density estimation by @schemaitat.
      • immunum-polars - high-performance plugin for antibody segmentation and numbering, with up to 1,000,000 antibodies per second on 48-core CPU machine.
      • flowview - A visual debugger that shows what happens at each step of your Polars DataFrame transformations in the terminal. By [@guillermodotn](https://github.com/guillermodotn).
      • polarise - A Polars-native DataFrame styling tool for HTML visualization by [@egayer](https://github.com/egayer).
      • polars-backtest - Polars extension for high-performance portfolio backtesting with Rust, Arrow, T+1 execution, and trade reports by [@Yvictor](https://github.com/Yvictor).
      • polarstation - Helper functions to simplify creating and working with Enums by [const-ae](https://github.com/const-ae).
      • 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](https://github.com/fcarvajalbrown).
      • PyCanopy - high-performance spatial query layer for Polars, competitive with industry SQL tools in performance
      • polars-skills - Official AI agent skills by [@polars-inc](https://github.com/polars-inc).
      • polars-mcp - A local MCP server for live API lookup against your installed Polars version by [@r-brink](https://github.com/r-brink).
      • quantwave - Polars-native technical analysis (221 indicators), execution-aware backtesting, and batch/streaming parity with a Rust core and agent skill by [@lavs9](https://github.com/lavs9).
      • polars-io-tools - Polars plugin extending lazy execution and predicate pushdown across external data sources (SQL, ClickHouse, Datadog, Delta Lake) by [@Point72](https://github.com/Point72/).
      • polarscope - Polars plugin for quick data summary, cleaning and visualization of Polars dataframes by @pytoned.
      • flexviz - Python library for interactive, cross-filterable charts on 100M+ rows, powered by lazy Polars aggregations and Rust kernels by [@jvdd](https://github.com/jvdd).
      • polars-mongo - Polars IO plugin that extends polars to read from mongodb collections via the LazyFrame apis by [@AThomas314](https://github.com/AThomas314).
      • 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-stats - Polars expression plugin that exposes scipy.stats-style probability distributions by [@FBruzzesi](https://github.com/FBruzzesi).
      • polars_streaming_csv_decompression
      • raffalib-python - [STATA](https://www.stata.com/)-like logging capabilities by [@raffaem](https://github.com/raffaem).

    • Python

      • polars for Python - [Python](https://www.python.org/) `polars` package to use polars DataFrame from Python.
      • Narwhals - Python files that provides an extremely lightweight compatibility layer between Polars, Pandas, cuDF, and Modin by [@MarcoGorelli](https://github.com/MarcoGorelli).

    • R

    • Ruby

      • polars for Ruby - [Ruby](https://www.ruby-lang.org/en/) `polars-df` gems to use Polars with Ruby.

    • Rust

      • GeoPolars - alpha Rust crate that extends the Polars DataFrame library for use with geospatial data (not in active development - see [top of readme](https://github.com/geopolars/geopolars)).
      • Polars CLI
      • iban_validation
      • plotlars
      • polars for Rust - [Rust](https://www.rust-lang.org/) `polars` crate to use polars DataFrame with Rust.
      • polars for Rust - [Rust](https://www.rust-lang.org/) `polars` crate to use polars DataFrame with Rust.

    • Scala/Java

      • scala-polars for Scala and Java - [Scala](https://scala-lang.org/) - [Java](https://www.java.com/fr/) `scala-polars` is a library for using Polars in Scala and Java projects by [@chitralverma](https://github.com/chitralverma).

  • Official documentation

  • Official news

  • Resources

    • 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](https://github.com/amitrathore) that introduces some basic features of Polars.
      • Polars-lazy - A blog post by [@ritchie46](https://github.com/ritchie46) and [@jorgecarleitao](https://github.com/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](https://github.com/braaannigan). Moreover, Liam also has a [Data Analysis with Polars](https://www.udemy.com/course/data-analysis-with-polars/?couponCode=DISCOUNTCODE) course on Udemy.
      • Youtube videos about Polars - A series of short youtube videos about Polars by [@braaannigan](https://github.com/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](https://github.com/JohnLockwood)
      • Discover the Power of Polars Library for Fast and Efficient Data Manipulation in Python - An article that quickly compares Polars to other data manipulation libraries by [Morpheus](https://medium.com/@morpheuX/about).
      • Why is Polars All The Rage? - An article that explains why Polars will become very popular by [SeattleDataGuy](https://substack.com/profile/4963622-seattledataguy) and [Daniel Beach](https://substack.com/profile/21715962-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](https://github.com/DataScienceDisciple).
      • Replacing Pandas with Polars. A Practical Guide - A blog post comparing some common functions between Pandas and Polars by [@danielbeach](https://github.com/danielbeach). Code used is available on Github [here](https://github.com/danielbeach/PandasVsPolars).
      • 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](https://github.com/danielbeach). Code used is available on Github [here](https://github.com/danielbeach/DataFrameShowDown).
      • 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](https://github.com/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](https://github.com/kahnwong/dataframe-frameworks-showdown).
      • Benchmarking PySpark Pandas, Pandas UDFs, and Fugue Polars - A blog post that compares the execution time of [fugue](https://github.com/fugue-project/fugue/) + Polars, Pandas UDFs and PySpark Pandas by [@kvnkho](https://github.com/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](https://github.com/makeuseofcode). Code used is available on [Github](https://github.com/makeuseofcode/Polars-vs-Pandas-Comparison).
      • 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](https://github.com/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](https://github.com/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](https://medium.com/@finndersen).
      • Pandas vs Polars vs Pandas 2.0 …. FIGHT - A blog post that does an ETL process for checking big data speed processing between Pandas, Pandas 2.0 and Polars by [@guoliveira](https://github.com/guoliveira).
      • Pandas vs Polars vs Pandas 2.0 … ROUND 2 - A blog post that makes a new comparison between Pandas, Pandas 2.0 and Polars by [@guoliveira](https://github.com/guoliveira).
      • Polars VS PySpark: Lazy Evaluation and Big Data - A blog post that compares lazy evaluation between Polars and Spark by [@guoliveira](https://github.com/guoliveira).
      • 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](https://github.com/MCodrescu). Code used is available on [Github](https://gist.github.com/MCodrescu/45e1adf1ca19863d566a0e0fcead5820).
      • A Polars exploration into Kedro - A blog post that explains how Polars can be used instead of pandas in [Kedro](https://kedro.org/) for your data catalog and data manipulation by [@astrojuanlu](https://github.com/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](https://github.com/jcanalesluna).
      • Lightning-fast queries with Polars - Another blog post that is a good introduction to Polars by [@astrojuanlu](https://github.com/astrojuanlu).
      • Polars – Laziness and SQL Context. - A blog post that presents two good reasons to adopt Polars : Lazy and SQL Context by [@danielbeach](https://github.com/danielbeach).
      • Exploring Polars - The Lightning-Fast DataFrame Library in Python - A blog post on the basics of Polars by [@mddas](https://github.com/mddas).
      • Pandas vs Polars – Speed Comparison - A blog post that compares the performance of Polars, Pandas and Pandas 2.0 by [@StuffbyYuki](https://github.com/StuffbyYuki). Code used is available on Github [here](https://github.com/StuffbyYuki/Python-Polars-Tips-and-Tricks/tree/main/pandas_vs_polars).
      • 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](https://github.com/StuffbyYuki). Code used is available on Github [here](https://github.com/StuffbyYuki/Python-Polars-Tips-and-Tricks/tree/main/lazyframe_vs_dataframe).
Programming Languages
Python 50 Rust 25 Jupyter Notebook 5 R 5 HTML 3 TypeScript 2 C# 1 Go 1 Ruby 1 Scala 1
Categories
Resources 913 Libraries/Packages/Scripts 139 Official documentation 13 Follow 10 Official news 6 Tools Built with Polars 4 Contributing 2 Tools build with Polars 2
Sub Categories
Blog posts 690 Tutorials & workshops 127 Polars plugins 120 Talks and videos 102 Ruby 6 R 6 Rust 6 Books 3 Cheat Sheets 3 Python 2 .NET 2 Node.js 1 Scala/Java 1 Go 1
Keywords
polars 37 rust 11 python 8 dataframe 6 polars-dataframe 5 arrow 4 r 4 data-science 4 pandas 3 polars-plugins 3 polars-extensions 3 validation 2 talib 2 dplyr 2 schema-inference 2 data-engineering 2 feature-engineering 2 data-analytics 1 dataengineering 1 cudf 1 dask 1 duckdb 1 ibis 1 pyarrow 1 pyspark 1 cosine-similarity 1 join 1 sparse-matrices 1 oreilly 1 oreilly-books 1 data-analysis 1 data-visualization 1 full-stack 1 react 1 tauri 1 datatable 1 tidyr 1 cookbook 1 expression 1 ta 1 benchmark 1 dfir 1 geoip 1 sql 1 time-series 1 dplyr-sql-backends 1 panel-data 1 big-data 1 machine-learning 1 dataframe-library 1