Replacing Pandas with Polars. A Practical Guide

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • normconf2022

  • Pandas

    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

  • > The big thing pandas has going for it is that it's already been through this field testing. All the bugs have been ironed out by the hundreds of thousands of users.

    At this very moment pandas github repo has 1563 open issues labeled with a bug tag [0]. So much for "all the bugs have been ironed out".

    [0] https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3...

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • fugue

    A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.

  • Fugue is an interesting library in this space , though I haven’t tried it

    https://github.com/fugue-project/fugue

    A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark, Dask and Ray without any rewrites.

  • polars

    Dataframes powered by a multithreaded, vectorized query engine, written in Rust

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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