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pandarallel: Pandas Multi-Core Acceleration in One Line

pandarallel: Pandas Multi-Core Acceleration in One Line

Pandarallel: Boost Pandas with parallel processing. One line of code. Multi-core speed & progress bars. Perfect for slow apply() operations.

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Meng Li
Aug 21, 2025
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pandarallel: Pandas Multi-Core Acceleration in One Line
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Introducing Pandarallel: Never Use The Apply Method In Pandas Again | by  Avi Chawla | TDS Archive | Medium

In simple terms: pandarallel is a lightweight weapon for parallelizing Pandas operations. Often just changing one line of code can utilize multiple cores, and it even displays progress bars.

Perfect for scenarios where row-by-row or group-by-group function processing is painfully slow. Yes, those painful scenarios where apply takes hundreds of milliseconds per row and the entire table takes half a day to process.

What is this tool? What pain points does it solve?

pandarallel is essentially a parallel framework (multiprocessing) layered on top of Pandas, turning common APIs like DataFrame/Series apply, map, groupby into parallel_xxx versions. Pain points it solves:

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