A curated list of Polars talks, tools, examples & articles. Contributions welcome !
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
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.
Official user guide for Python, Rust and R.
Official API Reference for Python.
Official API Reference for Rust.
Official API Reference for Node.js.
Official API Reference for R.
Official Polars Github repository.
Official blogs posts from Polars.
⏳ 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.
⏳ 28 min - Talk by @ritchie46 that introduces Polars and some of its design decisions.
Lazily read Stata, SAS, and fixed-width files in Polars by @alipatti.
Polars IO plugin to read SAS, Stata and SPSS file by @jrothbaum.
Guide to using the Python XlsxWriter library with Polars to create Excel reports.
Python package for reading tables from an Access database into Polars dataframes, using mdbtools by @DeflateAwning.
Polars plugin for reading CERN's ROOT file format by @DanielMaysWilliams.
Polars plugin for parsing FASTA and FASTQ files into DataFrames by @apcamargo.
Polars IO plugin for Redis - scan hashes, JSON, and other data types as LazyFrames with projection pushdown and RediSearch support by @joshrotenberg.
High-performance library for modifying Excel files with Polars.
Polars IO plugin that extends polars to read from mongodb collections via the LazyFrame apis by @AThomas314.
Polars plugin extending lazy execution and predicate pushdown across external data sources (SQL, ClickHouse, Datadog, Delta Lake) by @Point72.
tidypolars python library built on top of polars library that gives access to methods and functions familiar to R tidyverse users.
Ibis is a Python library that provides a lightweight, universal interface for data wrangling. It can be used with Polars.
Python package that provides a clean API for cleaning Polars DataFrame @pyjanitor-devs.
Python package for working with categorical data in Polars DataFrames by @machow.
Polars plugin for easily reordering DataFrame columns by @lmmx.
Polars plugin for flattening nested data by @lmmx.
Polars plugin providing a hopper of expressions for automatic, schema-aware application by @lmmx.
Python utility for programatically identifying differences between Polars DataFrames including schema differences, row-level mismatches, and column value changes by @Quantco.
Compare Dataframes to find difference in the schemas, rows and column values by @concur1.
Helper functions to simplify creating and working with Enums by const-ae.
Efficient hexagonal indexing for large-scale geospatial analysis by @Filimoa.
This plugin is an offline reverse geocoder for finding the closest city to a given (latitude, longitude) pair by @MarcoGorelli.
Polars plugin that provides geographical/spatial operations on Polars DataFrames, Series, and Expressions by @Oreilles.
Polars plugin for coordinates transformation and extractions features by @georgypv.
high-performance spatial query layer for Polars, competitive with industry SQL tools in performance
Polars plugin that makes Polars DataFrames generics by @baggiponte.
A package to facilitate validation of IBANs and getting bank identifier and branch identifier as a Polars plugin by @ericqu.
Polars plugin that provides schema and other rule validation for Polars DataFrames by @Quantco.
Decorator-first DataFrame contracts/validation (columns/dtypes/constraints) at function boundaries. Supports Polars/Pandas/PyArrow/Modin by @vertti.
Enterprise data quality framework with 289 validators, auto-profiling, and zero-configuration schema inference by @seadonggyun4.
Simple and flexible data contracts library, supports profiling and manually specified contracts in json, yaml or python by @benrutter.
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.
Polars plugin to parse/extract fields from urls by @condekind.
Polars plugin for IP address parsing and enrichment including geolocation by @erichutchins.
Polars plugins to apply gopher repetetition penalties and fasttext classifiers to text data by @Apsod.
Polars plugin for text similarity/pairwise distance functions by @ion-elgreco.
Python package for fuzzy matching with Polars, i.e. matching text elements that are similar but not exactly identical by bnm3k.
Polars plugin that computes string similarity measures directly on a Polars dataframe by @foxcroftjn.
Polars plugin that implements fast approximate joins on string columns for polars dataframes by @schemaitat.
Polars Time Series Extension that offers a wide range of metrics, feature extractors, and various tools for time series forecasting by @drumtorben.
Polars extension for Ta-Lib - support Ta-Lib functions in Polars expressions by @Yvictor.
Polars plugin with extra-datetime-related functionalities by @MarcoGorelli.
Polars plugin for business day arithmetic by @MarcoGorelli.
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 !
Polars plugin for machine learning by @barak1412.
Polars plugin for running candle ML models on Polars DataFrames by @wdoppenberg.
Polars extension for general data science use cases by @abstractqqq.
Polars plugin for embedding DataFrames by @lmmx.
Machine learning framework built with Polars by @AdrianAntico.
Scikit-learn pipeline compatible pre-processing steps by @azukds.
Polars plugin for interacting with LLMs in Polars by @daviddrummond95.
Official AI agent skills by @polars-inc.
A local MCP server for live API lookup against your installed Polars version by @r-brink.
Polars plugin for fast language identification by @rmalouf.
Polars plugin for embedding data with Sentence Transformers by @lmmx.
A collection of helpful polars plugins and functions for market data processing by @ngriffiths13.
Polars plugin exposing rust crate option-pricing by @oscar6echo.
Polars plugin for enriching orderbook data with best bid and offer information by @ChristopherRussell.
Polars plugin to calculate financial metrics by @LVG77.
Polars plugin that extracts Bloomberg’s financial data directly into polars.DataFrame by @MarekOzana.
Polars/Narwhals-centric tool for the analysis of financial time series data by @tschm.
Polars extension for high-performance portfolio backtesting with Rust, Arrow, T+1 execution, and trade reports by @Yvictor.
Polars-native technical analysis (221 indicators), execution-aware backtesting, and batch/streaming parity with a Rust core and agent skill by @lavs9.
Polars plugin for HTTP operations on columns by @lmmx.
Polars plugin that enables fast linear model Polar expressions by @azmyrajab.
Polars plugin that provides pairing functions that encode two natural numbers into a single natural number by @apcamargo.
Random number generation in Polars via the expression API by @alipatti.
Polars expression plugin that exposes scipy.stats-style probability distributions by @FBruzzesi.
Python polars package to use polars DataFrame from Python.
Collection of utilities for data exploration and analysis with Polars DataFrames by @junghoon-son.
Polars extension that provides a set of utilities for working with List-type columns in Polars DataFrames by @dashdeckers.
Polars helper methods to enhance developer productivity by @TomBurdge.
Polars plugin for persistent DataFrame-level metadata by @lmmx.
Polars IO plugin for reading compressed CSV/TSV files in a streaming fashion by @ghuls.
Polars plugin to showcase some features of the plugin system by @condekind.
Polars plugin for reading and writing avro files by @hafaio.
Python files that provides an extremely lightweight compatibility layer between Polars, Pandas, cuDF, and Modin by @narwhals-dev.
Python package that automatically upgrades your Polars code so it's compatible with future versions by @MarcoGorelli.
A lightweight utility library for writing Polars Expressions by @jrycw.
Polars plugin that implements the argpartition function by @GiovanniGiacometti.
Polars plugin with filesystem path utilities by @gorkaerana.
Fast JSON schema inference with support for Polars DataFrames by @lmmx.
Polars plugin that extends the capabilities of Polars with functionalities that are not currently found in Polars by @jrasband-dev.
Polars plugins for generating Polars expressions to work with nested data structures by @heshamdar.
Polars plugins with helper functions for feature engineering, using Polars by @AdrianAntico.
Facade to collect rows one-by-one into a Polars DataFrame with minimal overhead by @DeflateAwning.
Polars extension that provids a Map extension type and functions by @hafaio.
Polars plugin for kernel density estimation by @schemaitat.
Polars plugin for quick data summary, cleaning and visualization of Polars dataframes by @pytoned.
Python package to plot Polars DataFrames and LazyFrames with seaborn by @pavelcherepan.
Python package for fast and easy echarts with Polars backend by @AdrianAntico.
A visual debugger that shows what happens at each step of your Polars DataFrame transformations in the terminal. By @guillermodotn.
Python library for interactive, cross-filterable charts on 100M+ rows, powered by lazy Polars aggregations and Rust kernels by @jvdd.
A collection of Python Polars plugins and functions for market data processing by @ngriffiths13.
Polars plugin that extends Polars with encryption algorithm AES-GSM-SIV by @zlobendog.
Polars plugin for large-scale genomic analyses which is easy to use and considerably faster and more scalable than existing alternatives by @biodatageeks.
Python package for Processing IBAN, ISINs, URLs and other standard format data in Polars by @abstractqqq.
Python package that provides stable hashing functionality across different Polars versions by @ion-elgreco.
Python package that provides technical indicator operators rewritten in Polars by @wukan1986.
A pytest plugin library for doing snapshot testing with Polars DataFrames by @ngriffiths13.
Python package that prints Polars DataFrames with hierarchical headers by @rhshadrach.
Polars plugin for interconnection of graphs and networks with Frames by @t-ded.
Polars plugin for phonetic algorithms by @LeCodeMinister.
Polars plugin for determining if a date is a holiday by @mrjsj.
Polars plugin to automatically cache the result of expensive queries to disc by @alipatti.
Fast series hashing for polars, useful for caching by @paddymul.
STATA-like logging capabilities by @raffaem.
high-performance plugin for antibody segmentation and numbering, with up to 1,000,000 antibodies per second on 48-core CPU machine.
A Polars-native DataFrame styling tool for HTML visualization by @egayer.
Python polars package to use polars DataFrame from Python.
Polars CLI is a command line interface for running SQL queries with Polars as backend.
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 is a Rust library designed to facilitate the integration between the Polars data analysis library and Plotly library.
A package to facilitate validation of IBANs and getting bank identifier and branch identifier as a Polars plugin by @ericqu.
R rpolars package to use polars DataFrame from R.
tidypolars package to use polars with tidyverse syntax.
polarssql experimental package which is a DBI-compliant interface to Polars.
Dashboard comparing r-polars and py-polars APIs.
Next generation of Polars R API.
This project creates Go bindings for Polars.
Node.js nodejs-polars package to use polars DataFrame from Node.js.
Scala - Java scala-polars is a library for using Polars in Scala and Java projects by @chitralverma.
Ruby polars-df gems to use Polars with Ruby.
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.
A tool that aims to provide a lightweight GUI to data exploration/manipulation tasks using Rust Polars by @brutusyhy.
A CLI tool and Python library meant to perform large scale multiple association tests, primarily seen in academic research by @idinsmore1.
Pull, filter, and walk a GitHub user's repositories with Polars by @lmmx.
A tool to generate HTML/Markdown reports highlighting the differences between similar tables by @parker-research.
A lightweight tool for measuring the authoring complexity of Polars LazyFrame queries by @fran6w.
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.
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.
A Polars Cheat Sheet by @FranzDiebold.
A Cheat Sheet that shows how to convert some familiar Pandas commands to Polars by @braaannigan.
Quick reference guide for transforming, analyzing, and visualizing data with Python Polars by posit open source.
Book on using Python Polars for transforming, summarizing, and visualizing data.
Practical recipes for transforming and manipulating data with Polars.
Book focused on efficient, idiomatic data manipulation with Polars.
A side by side comparison between Polars and Pandas containing code in both frameworks by @kevinheavey.
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.
A notebook tutorial in French that illustrates the main features of Polars by @romaintailhurat and @linogaliana. There is also an accompanying blog post.
A page that explains how to rung Polars code distributedly with Fugue by @fugue-project.
A comprehensive, 2026-updated guide to flattening complex nested JSON structures and arrays natively in Polars.
A tutorial that explains how to display Polars dataframes with itables by @mwouts.
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.
A tutorial using Polars to implement a text processing pipeline process by @AntonsRuberts. Code used is available on Github here.
A side-by-side comparison of Polars, R base, dplyr and data.table packages by @ddotta.
A comprehensive workshop comparing Polars to Pandas, exploring a wide range of functions and features by @debnsuma.
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."
A tutorial that explains how to build data pipelines with Polars by @AntonsRuberts. Code used is available on Github here.
A tutorial that shows how to use Polars with Python ecosystem by @hfhoffman1144. Code used is available on Github here.
How you (yes, you!) can write a Polars Plugin by @MarcoGorelli.
Useful Python notebooks ordered by book chapter by @jeroenjanssens.
Collection of source code demonstrating tips and tricks in Polars by @StuffbyYuki.
Documentation that introduces the use of DuckDB and Polars with examples in R and Python by @grantmcdermott.
with Polars and Python. It also proposes some corrected exercices by @TLouf.
7-lesson online video course that covers various topics related todata manipulation with Polars by @cltrudeau.
List of articles published by @jorammutenge on linkedin #100DaysOfPolars.
A beginner tutorial to learn how to use Polars in Python by @datacamp.
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.
A blog post by Wei-Meng Lee to discover the basics of Polars and how it can be used in place of 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.
A blog post by @amitrathore that introduces some basic features of Polars.
A blog post by @ritchie46 and @jorgecarleitao that introduces Polars' lazy API in Rust.
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.
A series of short youtube videos about Polars by @braaannigan
An article that explores the Python Polars module as an alternative to Pandas, comparing their similarities and differences and providing some examples by @JohnLockwood
A blog post that evaluates Polars and Pandas in terms of I/O performance and speed when handling large datasets by Wes Poulsen.
An article that explains why Polars will become very popular by SeattleDataGuy and Daniel Beach.
An article that helps to understand key differences between Pandas and Polars Data Science libraries by @DataScienceDisciple.
A blog post comparing some common functions between Pandas and Polars by @danielbeach. Code used is available on Github here.
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.
A cheat sheet blog post of the most common Pandas operations translated into Polars by BexTuychiev.
A blog post that shows how to use Polars for initial data analysis and then effectively in production by @itamarst.
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.
A blog post that compares the execution time of fugue + Polars, Pandas UDFs and PySpark Pandas by @kvnkho.
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.
A blog post that analyzes in terms of Syntax, Speed, and Usability between Pandas 2.0 and Polars 0.17.0 by @priyanshu7401.
A blog post that describes why Polars could be a better alternative to pandas, dplyr or data.table by @DSkrzypiec.
A blog post that compares different ways (including Polars, pyarrow and C) to read a CSV file with Python by Finn Andersen.
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 blog post that explains how Polars can be used instead of pandas in Kedro for your data catalog and data manipulation by @astrojuanlu.
A blog post that compares differences between Python pandas 2.0 and Polars libraries by @jcanalesluna.
Another blog post that is a good introduction to Polars by @astrojuanlu.
A blog post that presents two good reasons to adopt Polars : Lazy and SQL Context by @danielbeach.
A blog post on the basics of Polars by @mddas.
A blog post that compares the performance of Polars, Pandas and Pandas 2.0 by @StuffbyYuki. Code used is available on Github here.
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.
A blog post that shows how to use the SQLContext object in Python to query a Polars DataFrame directly using SQL by @weimenglee.
A blog post that compares Polars and Pandas focusing in particular on optional dependencies by @ranggakd.
A blog post that describes the main data processing operations with Polars in Python by @AntonsRuberts. Code used is available in this notebook.
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.
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.
A blog post that presents some simple features of Polars using Python by Juveriya Mahreen.
A newsletter that compares the performance of Polars to Pandas for many common data manipulation techniques by PyQuant News.
A blog post that explores some deeper reasons behind the performance gains of Polars over Pandas.
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.
A blog post that compares Polars and DuckDB with pipelines for Data Engineering by @danielbeach.
A blog post that compares the run-time of reading a database into a dataframe using Pandas versus using Polars by Thomas Reid.
A blog post that explains how Polars works under the hood and th best use cases for Polars and Pandas by @t-redactyl.
A blog post that helps to understand how nested column types works in Polars by @braaannigan.
A blog post that compares Polars to DuckDB using Delta Lake by @wolliq.
A blog post that explains how to use Polars with Minio’s open-source object storage by @IndexSeek.
A blog post that explains how to partition large Polars DataFrames in AWS S3 by Matteo Arellano.
An article that presents how to use Polars in addition to Delta Lake by @danielbeach.
An article that explains how to learn fundamental Polars concepts with ChatGPT by Suhith Illesinghe.
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.
A blog post that compares Pandas2 and Polars for Feature Engineering tasks with Python by @hopswork.
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.
A blog post thats shows the use of Polars plugin system for Rust from some concrete examples by @ngriffiths13.
A blog post to helps you with the main operations that can be done with datetime data by Rielly Griffiths.
A short blog post that explains how to deal with temporal datasets by @gaborschulz. Full helpful notebook available here.
A blog post that describes the main features of Polars (with benchmarks) by ravi-m.
A blog post that deeps dive into some of the advanced data wrangling functionality in python’s Polars package by @emilyriederer.
A post that shows how Great Tables package uses polars expressions to make delightful tables by @machow.
A post that illustrates the possibility of extending the core Dataframe API of Polars with a few examples by @brunocous.
A post that depicts the 15 most common tabular operations in Polars and their corresponding translations in Pandas, SQL and PySpark by @ChawlaAvi.
A blog post that introduces LazyFrames with Polars an Python by Manoj Das.
A post that explains how to extract insightful information from your data in Polars by Alexandre Petit.
A post that explains how to Learn how to do group data using Polars by Alexandre Petit.
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.
A post that describs the process of "Polarification" of code written with Pandas by @duvenagep.
A science blog post that uses Polars to track the information for the molecules in DataFrames by @bertiewooster.
A post that demonstrates the usage of Polars with DuckDB to perform similar data transformations as is done using Pandas by @sumaniitm.
A post that compares Polars syntax to SQL by @bfeif.
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.
A blog post compares dataframe joins in Polars vs Pandas by @danielbeach.
An unofficial benchmark on DuckDB and Polars by @StuffbyYuki.
An article that compares Polars to Pandas with a dataset of 1.2 GB. Code used is available on Github here.
A reminder blog post that compares 30 functions written with Polars and Pandas by Yunuskaradagg.
A blog post that explores some common functions and their counterparts in both Polars and SQL by Yunuskaradagg.
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
An article that introduces to Polars design and its main features by @gox6.
An article that provides a comprehensive introduction of Polars, highlighting its features and showcasing practical examples to get started.
A post that illustrates how to use the polars_encryption plugin to encrypt data with Polars by @zlobendog.
An blog post that compares benchmarking scores with the Independent samples t-test and Welch’s t-test using Python.
A blog post that explains how to move from Pandas to Polars using Pycharm by [@Cheukting].
A blog post that provides a good first guide to the features of Polars by @AnsaBaby.
A blog post by the Polars team itself benchmarking Polars and Pandas.
A blog post that explains the reasons why Ari Lamstein now uses Polars by @arilamstein.
An article that presents data manipulation operations focusing on eager execution by Ardi Arunaditya.
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.
A blog post that compares performance on common data operations between Polars and Pandas by Vinod Chugani.
A blog post that talks about non-elementary group-by aggregations with Polars by @marcogorelli.
A blog post that that proposes 20 code translations from Pandas to Polars by @Rohit-Salunke.
A list of blog posts on Polars topics by @sparkbyexamples.
A post that covers practical techniques for managing missing data with Polars by Ian Eyre.
A short demo that introduces the Polars dataframe library through a marimo notebook by @rparkr.
A post that explains how to build a decision tree with Polars by @tocab. Code used is available on Github here.
A post that summarizes the main issues involved in the transition from Pandas to Polars by Michelangelo Florio.
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.
A 2025 benchmark that compares the performance of Polars and Pandas by @moncoachdata. Code used is available on Github here.
A tutorial article that shows how to migrate from Pandas to Polars with code examples and performance optimization tips by Vinod Chugani.
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.
A blog post list that details efficient transformation for Polars DataFrames from wide to long form by @samukweku.
A blog post that explains how using Polars increases code execution speed by 25 times compared to Pandas by @hatdropper1977.
A blog post that helps you choose between Polars and DuckDB based on use cases by @danielbeach.
An article that compares performance and features between Polars and Pandas in 2025 by @Gecofer.
An end 2025 beginner-friendly introduction to the Polars library in Python by Sara Jadhav.
A Databricks article comparing Pandas and Polars across performance, syntax, features, and use cases for Python data analysis by @databricks.
⏳ 37 min - Introduction to Polars by databricks.
⏳ 14 min - A short video tutorial to get started coding with Polars by @RobMulla.
⏳ 12 min - A video that compares Pandas, Spark and Polars for working with data in Python by @RobMulla.
⏳ 28 min - A video that reviews some alternatives to Pandas for Python and then demonstrates some Polars features by Juan Luis Cano Rodríguez.
⏳ 12 min - A video that provides an introduction to Polars for Python by @jeffheaton. Notebook used for the video in this github repo.
⏳ 57 min - A Polars tutorial series on Youtube by @martinbel. Notebooks and datasets used for the videos available in this github repo.
⏳ 37 min - A detailed video on Youtube that compares Polars and Pandas by @hu-po.
An article and a video ⏳ 19 min that explores some basic features of Polars by Frank Andrade.
⏳ 51 min - A detailed tutorial video in Spanish that shows 20 Polars functions to perform 80% of the tasks of a data scientist.
Great Polars introduction slides from @krlng at PyCon 2023.
⏳ 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.
⏳ 22 min - A video that presents 8 distinct tests which demonstrates differences between Pandas and Polars by @vb100. Associated github repo is here.
⏳ 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.
⏳ 4 min - A video that shows how to integrate Polars in a commande line interface by @paiml.
⏳ 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.
⏳ 41 min - A video that shows some basic manipulations with Polars and Python by @vedica1011. Notebook used for the video in this github repo.
⏳ 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.
⏳ 7 videos - A playlist of 7 videos that introduces the basic concepts of Polars (DataFrames, filtering, splitting...) by Joram Mutenge.
⏳ 6 videos - A playlist of 6 videos that analyzing and cleaning data using Polars to train machine learning models by Joram Mutenge.
⏳ 55 min - A podcast by The Developers' Bakery that compares the performance of Polars to Pandas by @MarcoGorelli.
⏳ 15 min - A video that presents Polars with Python by @enarroied. Article supplied with the video in this page.
⏳ 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 with organized by Python notebooks and chapter by @StuffbyYuki.
⏳ 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.
⏳ 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.
⏳ 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.
⏳ 12 min - A video that demonstrates how to integrate Polars with Ollama local models to do data analysis by @fahdmirza.
A playlist that introduces the basic features of Polars in an instructive way.
⏳ 20 min - A video that shows how to use SQL to query the data in Polars DataFrames by @bugbytes-io.
⏳ 110 min - A long video that explains and illustrates the basic principles of Polars by @KeithGalli. Associated github repo is here.
⏳ 19 min - A video that shows the usage of Polars with the Plotly graphic library by Plotly. <>
⏳ 29 min - A video that shows how to use Polars effectively for time series analysis iby @MarcoGorelli.
⏳ 65 min - A video that enables to learn practical techniques for data manipulation and advanced transformations by @kimfetti. Associated github repo is here.
⏳ 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.
⏳ 36 min - A video that explains how to understand expressions from a Pandas perspective by @marcogorelli.
⏳ 31 min - A video that explains how to write your own Polars Plugin by @marcogorelli.
⏳ 69 min - A video in which Ritchie Vink gives a look at Polars by Talk Python To Me.
⏳ 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.
Official Polars Github repository.
Author of Polars
Member of Polars organisation
Contributor to Polars projects
Contributor to Polars projects
Contributor to R Polars project
Contributor to R Polars project
Youtube Channel with thematic videos about Polars
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