A Comprehensive Guide to Using Polars for Fast, Efficient, and Easy Data Manipulation in Python
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This articles performs a benchmark against duckdb/polars/spark, with varying row count to see when each framework is more performant than others, with swap usage as another metric, in addition to runtime in seconds.
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Tutorial in the format of an ipynb notebook that illustrates several features of Polars in Spanish by @barbosarafael
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This is a side by side comparison between Polars and Pandas containing code in both frameworks, which I think pretty awesome. It can be viewed at a tutorial for those who intend to replace Pandas with Polars.
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A video that reviews some alternatives to Pandas for Python and then demonstrates some Polars features by Juan Luis Cano Rodríguez
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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. Code used is available on Github.
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Polars Introduction for Python with a 128GB Ryzen 24-core Benchmark vs Pandas
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If you're interested I can fork and create a PR if that's easier, or just let me know. Thanks -- great list. Will add to a forthcoming newsletter of mine.
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This is a series of blogpost on Polars usage which has a lot of useful tricks and information from @braaannigan. I also include website link including polars tag for easy navigation. Moreover, @braaannigan also has a Data Analysis with Polars course on Udemy.
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An article that helps to understand key differences between Pandans and Polars Data Science libraries by @DataScienceDisciple
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Article that explains why Polars will become very popular
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