# reiinakano/scikit-plot

An intuitive library to add plotting functionality to scikit-learn objects.

Repository: https://github.com/reiinakano/scikit-plot
Canonical: https://ross.abutalabs.com/products/scikit-plot
Language: Python
License: MIT
License Family: permissive
Topics: scikit-learn, visualization, machine-learning, data-science, plotting, plot
Last push: 2024-08-20T05:47:39+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3497, "days_push": 743, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2433, forks 285 (observed 2026-08-28T04:06:51.187036+00:00)

## What it is
Scikit-plot is a Python library that adds one-line plotting functions for common machine learning visualizations to scikit-learn objects, built on matplotlib. It covers plots like ROC curves, confusion matrix heatmaps, precision-recall curves, and learning curves with minimal boilerplate.

## Use cases
- plot roc curves for classification models
- visualize confusion matrix as a heatmap
- plot precision-recall curves
- generate learning curves for scikit-learn estimators
- quickly visualize machine learning evaluation metrics
- make presentation-ready ml plots with minimal code

## When to choose
- you use scikit-learn and want standard ML evaluation plots in one line
- you need quick, attractive matplotlib charts for model evaluation without boilerplate

## When to avoid
- you need interactive or web-based dashboards rather than static matplotlib figures
- you need highly customized or novel visualizations beyond the built-in plot types
- you don't use scikit-learn-style estimators

## Facets
- artifact type: library
- maturity: maintenance
- function: data-visualization, charts
- domain: machine-learning, data-science, data-visualization
- platform: python
- tags: scikit-learn, matplotlib, plotting, roc-curves, confusion-matrix

## Member repositories
- reiinakano/scikit-plot (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:51.187036+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:31:10.125870+00:00, confidence not recorded.
  - readme: https://github.com/reiinakano/scikit-plot (fetched 2026-08-28T04:06:51.187036+00:00, sha c5b17b1f6c98)
  - registry_pypi: https://pypi.org/pypi/scikit-plot/json (fetched 2026-08-29T10:12:34.137979+00:00, sha 41e94622873d)
- Data as of 2026-08-30T08:39:29.467469+00:00.