Individual skill
numpy-pro
NumPy guidance — array operations, broadcasting, vectorization, indexing, linear algebra, and performance.
skills/numpy-pro/SKILL.md
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## Overview
NumPy is the foundation of numerical Python: N-dimensional arrays, vectorized operations, and the broadcasting rules that make array code concise and fast. pandas, scikit-learn, and most scientific libraries are built on it — understanding NumPy deeply makes all of them clearer.
This skill covers the NumPy mental model: shapes and strides, broadcasting, advanced indexing, vectorization, linear algebra, and the performance practices (memory layout, views vs copies) that matter at scale.
## When to use
- Writing numerical/array code.
- Understanding broadcasting behavior.
- Vectorizing loops.
- Doing linear algebra (decompositions, solves, eigenvalues).
- Optimizing NumPy performance (views, contiguity, memory).
- Debugging shape mismatches.