# yhat/ggpy

ggplot port for python

Repository: https://github.com/yhat/ggpy
Canonical: https://ross.abutalabs.com/products/ggpy
Homepage: http://yhat.github.io/ggpy/
Language: Python
License: BSD-2-Clause
License Family: permissive
Archived: true
Last push: 2023-01-21T20:19:13+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4713, "days_push": 1320, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3687, forks 562 (observed 2026-08-28T04:08:14.677935+00:00)

## What it is
ggpy is a Python implementation of the grammar of graphics, inspired by R's ggplot2, built on pandas and matplotlib. It lets users declaratively compose plots with aesthetics, geoms, scales, and facets.

## Use cases
- create ggplot2-style plots in python
- make scatter plots and histograms with a grammar of graphics api
- facet plots by a categorical column
- apply color palettes and brewer scales to charts
- build density plots and boxplots from pandas dataframes

## When to choose
- you want ggplot2-like declarative plotting syntax in Python
- your data lives in pandas dataframes
- you prefer composable plot specifications over imperative matplotlib calls

## When to avoid
- you need actively maintained software with recent bug fixes
- you need the full feature set of ggplot2 from R
- you want interactive or web-based plotting rather than static matplotlib output

## Facets
- artifact type: library
- maturity: maintenance
- function: data-visualization, charts
- domain: data-visualization, data-science
- platform: python
- tags: grammar-of-graphics, ggplot2-port, plotting, matplotlib, pandas

## Member repositories
- yhat/ggpy (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:14.677935+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 2026-08-29T18:31:09.996249+00:00, confidence not recorded.
  - readme: https://github.com/yhat/ggpy (fetched 2026-08-28T04:08:14.677935+00:00, sha b1f79d4888b2)
  - homepage: http://yhat.github.io/ggpy/ (fetched 2026-08-29T09:24:55.483547+00:00, sha 54e119e97c45)
- Data as of 2026-08-30T08:39:29.467469+00:00.