NumPy
Foundational n-dimensional array library and the bedrock of scientific Python.
data-analysis-frameworksRecently released
83
Hero Score
Popularity
88
Performance
60
Ecosystem
100
Maturity
100
Dev Experience
65
⭐ 32,119 stars⬇ 215.3M downloads/wkFirst release: Jan 2006Last release: May 2026
Async Support: NoPlugin Extensions: Very highSpeed: Very fastDoc Quality: Very highLearning Curve: Medium
Pros
- • Foundational and ubiquitous across the scientific Python stack
- • Fast vectorized operations powered by a C-implemented core
- • Huge ecosystem of libraries built directly on top of it
Cons
- • Low-level arrays vs. higher-level DataFrame ergonomics
- • No built-in I/O conveniences like pandas (CSV, Excel, etc.)
- • Broadcasting and view/copy semantics can surprise newcomers