montanaflynn/stats
Some data may be outdated — see provenance labels.
A well tested and comprehensive Golang statistics library package with no dependencies. observed · 2026-09-22
Health v2 · maintenance only
96/100
- Activity 95
- Release rhythm 96
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: 7
- age_days: 4327
- days_rel: 31
- days_push: 31
- n_releases_24m: 14
Adoption not part of the score
3025 stars · 177 forks observed · 2026-09-22
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A comprehensive, dependency-free statistics library for Go providing descriptive statistics, correlation, regression, and related math functions. It is well tested and usable as a standard Go package/module.
Use cases
- compute median, mean, and percentiles in Go
- calculate correlation and covariance of datasets
- fit linear regression in a Go program
- round and clean numeric data in Go
- get summary statistics without external dependencies
When to choose
- you need statistics functions in a Go project with zero dependencies
- you want a small, well-tested, MIT-licensed stats package
- you need flexible input handling for mixed numeric data types
When to avoid
- you need advanced statistical modeling or distributions beyond descriptive stats
- you are working in a language other than Go
- you need GPU-accelerated or large-scale numerical computing
Facets
library · maturity stable
math data-science analytics data-science analytics go cross-platform statistics no-dependencies descriptive-statistics regression algorithms
1 source
- readme: https://github.com/montanaflynn/stats · fetched 2026-09-22 · bed3d3544a0a
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| montanaflynn/stats | main | 96 |
For agents
markdown · JSON · MCP: product_card(name="montanaflynn/stats")
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem