# BlakeRMills/MetBrewer

Color palette package in R inspired by works at the Metropolitan Museum of Art in New York

Repository: https://github.com/BlakeRMills/MetBrewer
Canonical: https://ross.abutalabs.com/products/metbrewer
Language: R
License: CC0-1.0
License Family: permissive
Topics: colorpalette, data-visualization, museums, python, r
Last push: 2025-01-03T16:52:43+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1726, "days_push": 607, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1268, forks 89 (observed 2026-08-28T04:04:11.437747+00:00)

## What it is
MetBrewer is a color palette library for R (with a Python port) offering palettes inspired by artworks at the Metropolitan Museum of Art. It includes colorblind-friendly checking and works with plotting workflows like ggplot2.

## Use cases
- find aesthetically pleasing color palettes for charts
- make ggplot2 plots with museum-inspired colors
- check if a palette is colorblind-friendly
- get continuous or discrete color scales in R
- use Met Museum palettes in Python matplotlib

## When to choose
- you want curated, art-inspired palettes for data visualization
- you need colorblind-friendly palette options
- you work in R or Python and want a simple palette helper

## When to avoid
- you need interactive or dynamic color theming tools
- you require palettes with strict perceptual uniformity like viridis

## Facets
- artifact type: library
- maturity: active
- function: data-visualization
- domain: data-visualization, data-science
- platform: python
- tags: color-palettes, colorblind-friendly, metropolitan-museum, ggplot2, aesthetics, r

## Member repositories
- BlakeRMills/MetBrewer (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:11.437747+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 2026-08-30T05:03:35.233056+00:00, confidence not recorded.
  - readme: https://github.com/BlakeRMills/MetBrewer (fetched 2026-08-28T04:04:11.437747+00:00, sha a9c0086ec58d)
- Data as of 2026-08-30T08:39:29.467469+00:00.