What it does

Takes a NumPy matrix or a pair of y_test/predictions vectors and draws a heatmap. That’s it. Two entry points: pp_matrix for DataFrames, pp_matrix_from_data for raw arrays. You pick a matplotlib colormap and optionally supply string labels for the axes.

The interesting bit

The whole pitch is “like Matlab” — which tells you something about how long Python’s default confusion-matrix plotting has been annoying people. The string-label handling is the practical win; no more squinting at “Class 0, Class 1…” when you meant Dog, Cat, Mouse.

Key highlights

• Accepts pre-built confusion matrices or computes one from two vectors
• Custom axis labels via DataFrame index/columns or a positional columns array
• Any matplotlib colormap, queried through standard colormaps list
• Published on PyPI as pretty-confusion-matrix
• Apache-licensed, with CI, code coverage, and a Zenodo DOI

Caveats

• README contains a broken image link (points to khuyentran1401 fork, not this repo)
• No API docs beyond the handful of examples shown; parameter reference is absent
• “Become a sponsor” section is longer than the usage instructions

Verdict

Grab it if you’re still hand-rolling sns.heatmap boilerplate for every model evaluation. Skip if you need normalized matrices, per-class metrics, or anything beyond a single pretty picture.