Descriptive statistics, correlation, linear regression, and the normal distribution in pure Python. No numpy/scipy, zero dependencies.
A pure-Python matrix library with NumPy-level linear algebra operations. Zero dependencies, readable implementations, full matrix operation suite including decompositions, solvers, and advanced linear algebra. Perfect for learning, constrained environments, or when you need transparent matrix operations without the NumPy ecosystem.
A lightweight Python library for matrix operations: creation (zero, identity, random), basic ops (access, copy), arithmetic (add, multiply, transpose, power), and advanced checks (square, trace, symmetric). Fully typed, validated, with comprehensive pytest test suite.
Small-matrix linear algebra in pure Python: arithmetic, transpose, determinant, inverse, and solving Ax=b. No numpy, zero dependencies.
Mini pandas + matplotlib in pure Python (no numpy/pandas/matplotlib). DataFrame, Series, groupby, merge, CSV/JSON I/O, statistics, and ASCII plotting. 72 tests.
Qubit State Algebra - Quantum runtime for regular computers
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