Chart selection references compared
Which reference to use when you must decide what chart to draw, and how to draw it well. Compared on 2026-10-30: the FT’s Chart Doctor Visual Vocabulary, From Data to Viz, Fundamentals of Data Visualization, Data Viz Project and the Data Visualisation Catalogue. Findings come from each site’s own pages and GitHub metadata.
Short answer
The FT Visual Vocabulary is still a good, widely cited chart chooser by task, but it is not the best single reference and it is not being developed: the poster is from 2016, and the repo’s last commit (2024-03-12) only added a German PDF. Use it to answer “what am I trying to show?”, pair it with From Data to Viz when you start from the shape of your data, and with Wilke’s book for the design principles the poster leaves out.
Comparison
| FT Chart Doctor / Visual Vocabulary | From Data to Viz | Fundamentals of Data Visualization | Data Viz Project | Data Visualisation Catalogue | |
|---|---|---|---|---|---|
| What it is | Poster and web page grouping chart types by purpose, with related reading | Decision tree from data type to candidate charts, with pitfalls | Free online book, 30 chapters, also sold in print by O’Reilly | Visual catalogue of chart types with filters | Catalogue of chart types, one page each |
| Made by | FT Visual Journalism Team | Yan Holtz and Conor Healy | Claus O. Wilke | Ferdio (infographic agency) | Not named on the home page |
| Starts from | The job: deviation, correlation, ranking, distribution, change over time, part-to-whole, magnitude, spatial, flow (FT README) | Your data type: numeric, categoric, both, maps, network, time series | Principles and a directory of visualizations | Input structure, function, shape, or family | Function, or an A-to-Z list |
| Size | Poster of chart types by group | About 39 graph types in 7 families | Three parts: from data to visualization, principles of figure design, miscellaneous | About 166 chart types (home page) | 60 chart types (home page) |
| Pitfalls and design advice | Light: links to research (Cleveland and McGill, Cairo, Wickham) | A gallery of 12 common mistakes, including cut y-axis, pie charts, rainbow palettes, overplotting | Strongest: proportional ink, overlap, colour pitfalls, redundant coding, multi-panel figures, no 3D | Little on the main page | Not visible on the home page |
| Code | D3 templates in a separate repo | Links to R, Python, D3.js and React tutorials | Source in R Markdown on GitHub | None on the main page | Not visible on the home page |
| Licence | MIT for the repo software (FT content stays copyright FT) | Not stated on the page; the repo is MIT | CC BY-NC-ND 4.0 (online manuscript) | Not stated | Not stated |
| Freshness (checked 2026-10-30) | Repo created 2016; last commit 2024-03-12; D3 repo last pushed 2021-08 | Copyright 2018 on the page; repo last pushed 2024-10-18 | Repo last pushed 2022-07; latest commit seen 2020-08-20 | No date on page | No year on page |
What each is best at
- FT Visual Vocabulary. Teaching people to recognise which job a chart does, in newsroom terms. It states it is not a how-to for making charts. It was inspired by Jon Schwabish and Severino Ribecca’s Graphic Continuum. Weakness: static and old, with no accessibility or colour guidance and no coverage of interactive or small-multiple design.
- From Data to Viz. Starting from a dataset and narrowing to a few chart types, with a mistakes gallery that explains why a tempting choice is wrong. Weakness: copyright is 2018 and the site promises no updates; its examples are in R.
- Fundamentals of Data Visualization. Learning why charts work or fail, with worked principles rather than a menu. Weakness: it is a book, not a lookup; the free online version is the author’s manuscript before final copy-editing, and the licence forbids derivatives.
- Data Viz Project. Browsing a very large range of chart forms for inspiration. Weakness: mostly a catalogue, with no selection guidance on the main page, and run by an agency that sells visualization services.
- Data Visualisation Catalogue. A compact A-to-Z reference. I could confirm only the list of 60 types, not what each page covers.
Which one when
| You are | Use |
|---|---|
| Deciding what to show before you have a chart in mind | FT Visual Vocabulary |
| Holding a dataset and unsure what chart fits | From Data to Viz |
| Chart is chosen but looks wrong, cluttered or misleading | Wilke, parts II and I |
| Hunting for an unusual form (e.g. an arc diagram) | Data Viz Project or the Catalogue |
| Teaching a newsroom or team chart literacy | FT Visual Vocabulary, then Wilke |
Limits to know
- The comparison rests on each site’s own pages and GitHub metadata. Individual chart pages in the Data Viz Project and the Data Visualisation Catalogue, the poster PDF and Wilke’s chapters were not read in full.
- The FT Chart Doctor column on ft.com is behind a paywall, so how recent the column is was not checked.
- Datawrapper’s guides, Edward Tufte’s books and Cole Nussbaumer Knaflic’s Storytelling with Data are not covered.
Related
- Open-source BI comparison, Apache Superset and Metabase (tools for building the charts)
Sources
- https://github.com/Financial-Times/chart-doctor and its
visual-vocabulary/README.md - https://github.com/ft-interactive/visual-vocabulary
- https://www.data-to-viz.com and https://github.com/holtzy/data_to_viz
- https://clauswilke.com/dataviz and https://github.com/clauswilke/dataviz
- https://datavizproject.com
- https://datavizcatalogue.com
- https://www.datawrapper.de/academy