Why learn Pandas & NumPy?
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The default toolkit for tabular data in Python.
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Used by analysts, scientists, and ML engineers daily.
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Replaces spreadsheets for any non-trivial dataset.
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Foundation for everything from EDA to ML feature engineering.
What you can build with Pandas & NumPy
Cleaning and exploring datasets ETL and data pipelines Feature engineering for ML Reporting and ad-hoc analysis
Pandas & NumPy tutorials
2 articlesHand-written tutorials, ordered as a recommended learning path.
- 01 DataFrames Basics A practical guide to the daily DataFrame moves — read_csv and read_json, head and info, column selection, loc vs iloc, boolean filtering, sorting, and value_counts.
- 02 groupby & merge A practical guide to combining and summarising DataFrames — groupby with named aggregations, multi-column aggregates, the four merge styles, and stacking with concat.