Python Polars: The Definitive Cheatsheet

Python Polars Cheatsheet (based on our O'Reilly book)

Python Polars: The Definitive Cheatsheet

Polars is a fast, expressive DataFrame library for Python, offering both eager and lazy APIs. This cheatsheet, based on the O'Reilly book, covers data structures, data types, reading/writing data, and key transformations like selecting, filtering, aggregating, and reshaping. It highlights Polars' advantages over pandas, such as no row index, immutability, and an optimizer that applies predicate and projection pushdowns. Includes practical examples and tips for handling large datasets with the streaming engine.

The optimizer automatically applies predicate pushdown (filtering as early as possible) and projection pushdown (dropping columns that are never used).
  1. jeroenjanssens

    We spent the last few weeks compressing our book, Python Polars: The Definitive Guide (nearly 500 pages), down to a two-page cheatsheet. It's a highly lossy compression, but hopefully a useful one! Besides the PDF, there's also an accessible HTML version.

    We're curious to hear what you think. Let us know if we missed any of your favorite Polars operations, or if you have any feedback on how we organized it.

  2. wsowens

    Despite writing most of my procedural code in Python, I've always preferred doing my data analysis in R. For all of R's warts, the ergonomics of the dplyr + ggplot + the rest of the tidyverse are very tough to beat. My few attempts to use Pandas and matplotlib/seaborne have always proved frustrating. Based on this cheatsheet though, it seems like Polars addresses some of the friction of Pandas. Looking forward to trying it!

  3. clircle

    I get that the data science world has moved on to python, but I always felt that R's data.table had the slickest dataframe developer experience. I have toyed with Polars for a few hours, maybe I should give it a better chance.

  4. paulfharrison

    I'm sure Polars is great, but I can't get over needing 10 characters of ceremony every time I want to refer to a column in a data frame.

    pl.col("...")

  5. mrtimo

    I've moved from python/polars/pandas to DuckDB and have not looked back

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2026-08-18