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Pandas & NumPy

Data manipulation in Python with Pandas and NumPy.

Why learn Pandas & NumPy?

  • The default toolkit for tabular data in Python.

  • Used by analysts, scientists, and ML engineers daily.

  • Replaces spreadsheets for any non-trivial dataset.

  • 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 articles

Hand-written tutorials, ordered as a recommended learning path.

  1. 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.
  2. 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.