---
title: "Data Visualisation"
source: The Turing Way
source_url: https://github.com/the-turing-way/the-turing-way
licence: CC-BY-4.0
domain: data-and-analysis
subdomain: turing-way
date_added: 2026-04-25
---

(rr-rdm-visualisation)=
# Data Visualisation

Data visualisation allows you to: 
* Extract valuable information and patterns from data
* Communicate this in a clear and comprehensible visual representation
* Enhance the communication of research findings, making it accessible to a broader audience
* Identify data quality issues, as outliers and data errors may become more visible in visualisations

Therefore, data visualisation is an aspect of research data management!

Below follow some resources that may help you in creating clearer, more accessible and more transparent data visualisations. 


(rr-rdm-visualisation-tools)=
## Tools

-  [Datawrapper](https://www.datawrapper.de/), where you can upload your data to generate tables and charts.
-  [upset graphs](https://upset.app/) are a straightforward way to visualize set intersections in a matrix layout, which can help in analysing multiple datasets at once.
-  Using **Python Plotly** you can add annotations and animations as extra visual cues to highlight important features.
  - [Annotating visualisations in Python plotly](https://medium.com/nerd-for-tech/enriching-data-visualizations-with-annotations-in-plotly-using-python-6127ff6e0f80) (blog and video)
  - [Animations using Python plotly](https://youtu.be/kMFvpmOaF2I)

(rr-rdm-visualisation-accessibility)=
## Accessibility

- [Tips to improve interpretability and accessibility](https://www.youtube.com/watch?v=RzT95DVUMnw) by Dr Tracey Weissgerber (video)
- [Writing Meaningful Alt-Texts for Data Visualisations in R](https://www.youtube.com/watch?v=dXV5bx1WQTM)
- Writing Alt Text to communicate the meaning in data visualizations by @Hare2022dataviz
- [Alt-texts](https://axesslab.com/alt-texts/)
- [Writing Alt Text](https://dataabinitio.com/?p=1161) for a Scientific Figure by Kristin Briney
- [Writing Alt Text for Data Visualization](https://medium.com/nightingale/writing-alt-text-for-data-visualization-2a218ef43f81)
  To get started, use Amy Cesal's quick formula: [alt text = `chart type` of `type of data` where `reason for including chart`. `Link to data`.]

(rr-rdm-visualisation-colours)=
## Colours
- [A detailed guide to colors in data vis style guides](https://blog.datawrapper.de/colors-for-data-vis-style-guides/) (blog)

(rr-rdm-visualisation-resources)=
## Resources

### Books and Articles

- [Fundamentals of Data Visualisation](https://serialmentor.com/dataviz/) by {cite:ps}`Wilke2019dataviz`
- Data Visualisation, A practical introduction by @Healy2018dataviz
- Creating clear and informative image-based figures for scientific publications by @Jambor2021dataviz
- A layered grammar of graphics by @Wickham2010dataviz
- A Field Guide to Digital Color by @Stone2003dataviz
- The Grammar of Graphics by @Wilkinson1999dataviz
- The Visual Display of Quantitative Information by @Tufte2001dataviz
- Avoiding Twisted Pixels: Ethical Guidelines for the Appropriate Use and Manipulation of Scientific Digital Images by [](https://doi.org/10.1007/s11948-010-9201-y)

### Other text resources and examples

- [Data Visualisation Course](https://exploratory-data-visualization.netlify.app/)
- [Free visual and communication resources](https://padlet.com/evansemporiumstore/lks3aoyyhkpnkmpe)
- [A collection of notebooks demonstrating plotting with matplotlib](https://github.com/KirstieJane/NH19-Visualization/)
- [A Comprehensive Guide to the Grammar of Graphics for Effective Visualization of Multi-dimensional Data](https://towardsdatascience.com/a-comprehensive-guide-to-the-grammar-of-graphics-for-effective-visualization-of-multi-dimensional-1f92b4ed4149)
- [Friends Don't let Friends Write Bad Graphs](https://github.com/cxli233/FriendsDontLetFriends) by @li2023dataviz
- [Data by Design](https://dataxdesign.io/)
- [Parallel Coordinates Plots (PCP)](https://visualizationcheatsheets.github.io/pcp.html)
- [I’ve Stopped Using Box Plots. Should You?](https://nightingaledvs.com/ive-stopped-using-box-plots-should-you/)

### Videos

- 5 minute videos on [Data visualisation - Introduction and motivation](https://www.youtube.com/watch?v=7t2qYO2zEWQ) and [Figure design, design process, fundamentals](https://www.youtube.com/watch?v=WtYArH4EIRg)
- [Create Effective Data Visualizations](https://youtu.be/jt-VdyFzjj0) (second part focuses primarily on Tableau)
- [Data visualisation for scientific papers](https://www.youtube.com/playlist?list=PLWb8IFSVeQ62NbG-u4vQlh4srFcC2KH5g) videos by ReproducibiliTeach
- Outline of grammar of graphics
    -   [A Grammar of Graphics](https://www.youtube.com/watch?v=RCaFBJWXfZc) - Excellent summary of the grammar of graphics layers or 'functional pipeline'
    -   [Leland Wilkinson - The Grammar of Graphics](https://www.youtube.com/watch?v=1X93Sum_SyM) - Leland himself giving a quick high level summary of the grammar of graphics
-   [Martin Krzywinski: A pandemic of bad charts](https://www.youtube.com/watch?v=_YGmfsKL8N8)
-   [EMBL Keynote Lecture 2019 - Data visualization and data science, Hadley Wickham](https://www.youtube.com/watch?v=9YTNYT1maa4)
-   Practical high level intros to Tufte's principles
    -   [What should we do to improve our graphics and figures?](https://www.youtube.com/watch?v=00Fha1lkRxk)
    -   [Graphical Excellence](https://www.youtube.com/watch?v=VkyzSAPkQ50)
- Workshop: [Missing Data Exploration, Imputation, and Evaluation](https://www.youtube.com/watch?v=MTHgZNB5Wxw) by Hanne Oberman
- [Violin plots should not exist](https://www.youtube.com/watch?v=_0QMKFzW9fw) by Angela Collier 

### Podcasts

-   [Data Viz Today](https://dataviztoday.com/)
-   [Data Stories](https://datastori.es/)
-   [PolicyViz](https://policyviz.com/podcast/)

### Other

-   [biovis](http://biovis.net/)
