A practical guide to using Jupyter's %timeit magic for accurate Python benchmarking, including setup handling, common pitfalls, and verification steps.

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notebook-timing code-optimization python-performance

Tasadduq Burneyowner

Started11 May 2026, 23:07 UTC

Level 36Owner31,775 rep points

Community & Careers

Article1 reply1 comment2,659 followingPosted 27 Feb 2026, 14:45 UTC26K views2,168 votes

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Stop Using .apply(): Speeding Up Pandas with Vectorization

Stop relying on .apply() for data transformations. Learn how to use NumPy-backed vectorization and boolean masking to process millions of rows in milliseconds instead of minutes.

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pandas python-performance data-engineering

Tasadduq Burneyowner

Started27 Feb 2026, 14:45 UTC

Level 36Owner31,775 rep points

Zohahelper

commented27 Feb 2026, 15:18 UTC

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