📘 Notes

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Structured Python data-analytics notes — NumPy, Matplotlib, and Pandas — 8 lessons across 3 chapters. Each file covers one topic and links to its matching exercise file at the bottom. Assumes chapters 01–08 of the companion Python Fundamentals course.

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01 — NumPy

File	Topic
01-01-numpy-intro.md	ndarray creation, dtypes, arange, linspace, zeros/ones/eye, reshape
01-02-numpy-array-operations.md	Element-wise arithmetic, broadcasting, math functions, where, clip, sort
01-03-numpy-slicing-and-indexing.md	Slicing, views vs copies, boolean indexing, fancy indexing, where, isin
01-04-numpy-2d-arrays.md	Matrix creation, 2D indexing, row/col stats, transpose, dot product, stacking
01-05-numpy-statistics.md	Descriptive stats, percentiles, population vs sample, cumsum, normalization, distributions

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02 — Matplotlib

File	Topic
02-01-matplotlib-basics.md	Line, scatter, bar, histogram plots; subplots; labels, legends, grids; saving

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03 — Pandas

File	Topic
03-01-pandas-basics.md	Series, DataFrame, filtering, sorting, add/drop columns, apply, CSV I/O
03-02-pandas-data-manipulation.md	groupby, merge, concat, pivot tables, melt, .str, missing values