# Financial-Times/chart-doctor

Sample files to accompany the FT's Chart Doctor column

Repository: https://github.com/Financial-Times/chart-doctor
Canonical: https://ross.abutalabs.com/products/chart-doctor
Language: HTML
License: MIT
License Family: permissive
Last push: 2024-03-12T17:12:50+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": 3737, "days_push": 904, "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 3326, forks 507 (observed 2026-08-28T04:07:56.474225+00:00)

## What it is
A collection of sample files and example code accompanying the Financial Times' Chart Doctor column on data visualization and chart-making. It serves as supplementary learning material for data journalists and visualization practitioners.

## Use cases
- learn data visualization techniques from FT chart examples
- find sample code for building charts in D3
- study data journalism chart design patterns
- reproduce charts from the FT Chart Doctor column
- learn dataviz best practices with worked examples

## When to choose
- you read the FT Chart Doctor column and want the accompanying code
- you are a data journalist learning visualization techniques
- you want practical, real-world dataviz examples

## When to avoid
- you need a production charting library or framework
- you want a maintained tool with API guarantees rather than tutorial samples

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-visualization, charts, developer-tools
- domain: data-visualization, tutorials, education
- platform: cross-platform
- tags: data-journalism, dataviz, tutorials, financial-times, sample-code, html, d3, web

## Member repositories
- Financial-Times/chart-doctor (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:56.474225+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 2026-08-29T18:41:46.306227+00:00, confidence not recorded.
  - readme: https://github.com/Financial-Times/chart-doctor (fetched 2026-08-28T04:07:56.474225+00:00, sha e5f720d3a87d)
- Data as of 2026-08-30T08:39:29.467469+00:00.