Polars
pola.rs
Polars — DataFrames for the new era
Polars is a high-performance DataFrame library for Python and Rust. Built on Apache Arrow, it's the fastest way to work with tabular data at any scale.
Reddit
reddit.com › r/dataengineering › i'm sceptic about polars
r/dataengineering on Reddit: I'm sceptic about polars
July 17, 2024 -
I've first heard about polars about a year ago, and It's been popping up in my feeds more and more recently.
But I'm just not sold on it. I'm failing to see exactly what role it is supposed to fit.
The main selling point for this lib seems to be the performance improvement over python. The benchmarks I've seen show polars to be about 2x faster than pandas. At best, for some specific problems, it is 4x faster.
But here's the deal, for small problems, that performance gains is not even noticeable. And if you get to the point where this starts to make a difference, then you are getting into pyspark territory anyway. A 2x performance improvement is not going to save you from that.
Besides pandas is already fast enough for what it does (a small-data library) and has a very rich ecosystem, working well with visualization, statistics and ML libraries. And in my opinion it is not worth splitting said ecosystem for polars.
What are your perspective on this? Did a lose the plot at some point? Which use cases actually make polars worth it?
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I went Polars for the syntax, not for the speed tbh
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For the size of data we work with, (100s of GB), Polars is the best choice. Pandas would on choke data that size. Spark would be overkill for us. We can run Polars on a single machine without the hassle of setting up and maintaining a Spark cluster. From my experience Polars is orders of magnitude faster than Pandas (when Pandas doesn't choke altogether). Polars has the additional advantage that its API encourages you to write good clean code. Optimization is done for you without having to resort to coding tricks. In my opinion it's advantages will eventually lead to Polars edging out Pandas in the dataframe library space.
I recorded a crash course on Polars library of Python (Great library for working with big data) and uploaded it on Youtube
Is polars really this popular now or is everyone on reddit on their payroll More on reddit.com
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December 19, 2023Newest 'python-polars' Questions - Stack Overflow
Stack Overflow | The World’s Largest Online Community for Developers More on stackoverflow.com
Is anyone using Polars in Prod?
No issues, it's awesome, especially the LazyFrames. Why Pandas would be okay and Polars wouldn't? I don't remember the last time I used something other than Polars for dataframe manipulation/Parquet files in Python. Just use it for everything! Filtering is really powerful. More on reddit.com
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January 8, 2025Why are more people not excited by Polars?
Polars is very new. That's your answer. Even if a tool like Polars is demonstrably good, or better, than another it takes time for it to gain a foothold. Maybe, when it's more complete, stable, and battle tested by early adopters like yourself, it will have a place in more DE ecosystems. More on reddit.com
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April 30, 202508:19
Working With Python Polars: Getting Started with DataFrames - YouTube
Learning the Polars DataFrame Library!
Polars: The Next Big Python Data Science Library... written in ...
01:49:41
Learning the Polars DataFrame Library! - YouTube
Lewis Menelaws | Polar’s is a python package meant for ...
GitHub
github.com › pola-rs › polars
GitHub - pola-rs/polars: Extremely fast Query Engine for DataFrames, written in Rust · GitHub
1 week ago - However, both the Python package and the Python module are named polars, so you can pip install polars and import polars.
Author pola-rs
Databricks
databricks.com › blog › polars-vs-pandas
Polars vs Pandas | Databricks
Pandas enjoys extensive documentation, community support and mature plotting libraries. It’s popular for small-to-medium sized datasets and exploratory analysis. Polars is a fast, Rust-based, columnar DataFrame library with a Python API.
PyPI
pypi.org › project › polars
polars · PyPI
Note that the Rust crate implementing the Python bindings is called py-polars to distinguish from the wrapped Rust crate polars itself.
» pip install polars
Wikipedia
en.wikipedia.org › wiki › Polars_(software)
Polars (software) - Wikipedia
May 27, 2026 - Polars is an open-source software library for data manipulation. Polars is built with an OLAP query engine implemented in Rust using Apache Arrow Columnar Format as the memory model. Although built using Rust, there are Python, Node.js, R, and SQL API interfaces to use Polars.
DataCamp
datacamp.com › tutorial › python-polars-tutorial-complete-guide-for-beginners
Python Polars Tutorial: A Complete Guide for Beginners | DataCamp
November 13, 2025 - In the world of data analysis, pandas has long been the default choice for handling tabular data in Python by data professionals. However, as datasets grow in size and complexity, pandas can encounter performance bottlenecks, limited multi-core utilization, and memory constraints. This is where Polars emerges as a modern alternative.
Medium
cliffy-gardens.medium.com › using-python-polars-my-late-2024-review-da806618a102
Using Python Polars — My (Late) 2024 Review | by Cliff Chew | Medium
September 25, 2024 - About a year ago, I heard about Polars, a new data processing Python package written in Rust that is much faster than Pandas. Back then…
Real Python
realpython.com › polars-python
Python Polars: A Lightning-Fast DataFrame Library – Real Python
August 10, 2023 - Welcome to the world of Polars, a powerful DataFrame library for Python! In this showcase tutorial, you'll get a hands-on introduction to Polars' core features and see why this library is catching so much buzz.
Practical Business Python
pbpython.com › polars-intro.html
Introduction to Polars - Practical Business Python
January 14, 2024 - The Modern Polars resource goes into a much more detailed look at how to work with pandas and polars with code examples side by side. It’s a top notch resource. You should definitely check it out. Pandas has been the go-to data analysis tool in the python ecosystem for over a decade.
GeeksforGeeks
geeksforgeeks.org › python › an-introduction-to-polars-pythons-tool-for-large-scale-data-analysis
An Introduction to Polars: Python's Tool for Large-Scale Data Analysis - GeeksforGeeks
July 23, 2025 - Polars is a blazingly fast Data Manipulation library for Python, specifically designed for handling large datasets with efficiency. It leverages Rust's memory model and parallel processing capabilities, offering significant performance advantages ...
freeCodeCamp
freecodecamp.org › news › how-to-use-the-polars-library-in-python-for-data-analysis
How to Use the Polars Library in Python for Data Analysis
December 10, 2025 - In this article, I’ll give you a beginner-friendly introduction to the Polars library in Python. Polars is an open-source library, originally written in Rust, which makes data wrangling easier in Python. The syntax of Polars is very similar ...
Reddit
reddit.com › r/python › i recorded a crash course on polars library of python (great library for working with big data) and uploaded it on youtube
r/Python on Reddit: I recorded a crash course on Polars library of Python (Great library for working with big data) and uploaded it on Youtube
December 19, 2023 -
Hello everyone, I created a crash course of Polars library of Python and talked about data types in Polars, reading and writing operations, file handling, and powerful data manipulation techniques. I am leaving the link, have a great day!!
https://www.youtube.com/watch?v=aiHSMYvoqYE&list=PLTsu3dft3CWiow7L7WrCd27ohlra_5PGH&index=6&t=689s
Stack Overflow
stackoverflow.com › questions › tagged › python-polars
Newest 'python-polars' Questions - Stack Overflow
Lets say we wanted to find the most amount of consecutive 1's row by row, with the below df. import polars as pl df = pl.from_repr(""" ┌─────┬─────┬─────┬─────┬─────┐ │ 0 ┆ 1 ┆ 2 ...
DataCamp
datacamp.com › blog › an-introduction-to-polars-python-s-tool-for-large-scale-data-analysis
An Introduction to Polars: Python's Tool for Large-Scale Data Analysis | DataCamp
June 6, 2023 - Polars is a DataFrame library completely written in Rust and is built to empower Python developers with a scalable and efficient framework for handling data and is considered as an alternative to the very popular pandas library.
KDnuggets
kdnuggets.com › pandas-vs-polars-a-complete-comparison-of-syntax-speed-and-memory
Pandas vs. Polars: A Complete Comparison of Syntax, Speed, and Memory - KDnuggets
March 5, 2026 - For the most accurate comparisons, tests should ideally be run in separate, isolated Python processes. Now let's look at how syntax differs between the two libraries. We'll cover the most common operations you'll use. Let’s select a subset of columns. We’ll create a much smaller DataFrame for this (and subsequent examples). import pandas as pd import polars as pl # Create sample data data = { 'name': ['Anna', 'Betty', 'Cathy'], 'age': [25, 30, 35], 'salary': [50000, 60000, 70000] } # Pandas approach df_pandas = pd.DataFrame(data) result_pandas = df_pandas[['name', 'salary']] # Polars approach df_polars = pl.DataFrame(data) result_polars = df_polars.select(['name', 'salary']) # Alternative: More expressive result_polars_alt = df_polars.select([pl.col('name'), pl.col('salary')]) print("Pandas result:") print(result_pandas) print("\nPolars result:") print(result_polars)
Towards Data Science
towardsdatascience.com › home › latest › modern dataframes in python: a hands-on tutorial with polars and duckdb
Modern DataFrames in Python: A Hands-On Tutorial with Polars and DuckDB | Towards Data Science
November 21, 2025 - Basically, each of them has its own superpower. Polars is the speedster, and DuckDB is kind of like the memory magician. And the best part? Both integrate seamlessly with Python, allowing you to enhance your workflows without a complete rewrite.
Polars
docs.pola.rs › user-guide › expressions › lists-and-arrays
Lists and arrays - Polars user guide
In general, Polars does not infer that a column has the data type Array for performance reasons, and defaults to the appropriate variant of the data type List. In Python, an exception to this rule is when you provide a NumPy array to build a column.
Deepnote
deepnote.com › blog › ultimate-guide-to-the-polars-library-in-python
Ultimate guide to the polars library in python
August 22, 2025 - Polars is a high-performance dataframe library for Python that brings a modern, columnar, and expression-driven approach to data wrangling and analytics.
Pola-rs
pola-rs.github.io › r-polars
Polars R Package
It can be used to process Polars DataFrames and other data structures, convert objects between Polars and R, and can be integrated with other common R packages. To learn more, read the online documentation for this R package, and the user guide for Python/Rust Polars.