Data Visualisation: Principles and practice

4th GM Analyst Network meetup, 17-05-2018, Manchester Metropolitan University.

Transcript

1. Henry Partridge GM Analyst Network Data Visualisation: Principles and practice Data Lab Manager 17 May 2018
2. Trafford Data Lab https://www.trafforddatalab.io/
3. • Clarity • Openness • Reproducibility Principles
4. Clarity
5. We strive for an economy of style in all of our data visualisations.
6. “Chart time! It's first Q shipping it garnered 19% market share, Palm 9.8%, RIM 39%, other 20%, Nokia 7% …" Macworld 2008 keynote Source: Macworld 2008 keynote; www.engadget.com
7. Cleveland’s perceptual hierarchy 1 Position along a common scale Scatter plots 2 Positions along non-aligned, identical scales Small multiples 3 Length, direction, angle Waterfall chart 4 Area Treemap 5 Volume, curvature 3D bar charts 6 Shading, colour saturation Continuous color scale Source: Cleveland and McGill (1984) Accuracy
8. Pie chart vs bar chart Source: Cleveland and McGill (1984: 533)
9. “A table is nearly always better than a dumb pie chart; the only worse design than a pie chart is several of them, for then the viewer is asked to compare quantities located in spatial disarray both within and between charts […] Given their low density and failure to order numbers along a visual dimension, pie charts should never be used.” — Edward Tufte (1983)
10. Tufte’s aesthetic guidelines
11. Tufte’s aesthetic guidelines
12. Wilkinson’s Grammar of Graphics Source: Wilkinson (2005) "A statistical graphic is a mapping from data to aesthetic attributes (colour, shape, size) of geometric objects (points, lines, bars)." — Hadley Wickham (2016)
13. Rosling’s bubble charts Source: gapminder.org Variable Geometry Aesthetic GDP per capita ($) point x-position Life Expectancy point y-position Population point size Continent point fill
14. Rosling’s bubble charts in ggplot2 Source: gapminder.org
15. Lab visualisation style </> https://traffordDataLab.io/assets/theme/ggplot2/theme_lab.R
16. Lab visualisation style </> https://www.trafforddatalab.io/info/community_safety/burglary/index
17. Openness
18. We are committed to the sourcing, preparation and publication of open data.
19. 5-star Open Data Source: http://5stardata.info/en/
20. Defibrillators Source: https://www.trafforddatalab.io/maps/explore/
21. Open data portal Source: https://www.trafforddatalab.io/data
22. Reproducibility
23. We will publish the data and code that drive our data visualisations.
24. Example visualisation </> https://www.trafforddatalab.io/info/demographics/languages/R/fig1.R
25. Data Source: https://www.trafforddatalab.io/info/demographics/languages
26. Image Source: https://www.trafforddatalab.io/info/demographics/languages
27. R code Source: https://www.trafforddatalab.io/info/demographics/languages
28. R and (RStudio)
29. • Re-run code or adapt with different data • R is a language so it is readable as text • Post R code via Twitter, reddit, email etc Reproducibility in R
30. Graphics companion Source: https://www.trafforddatalab.io/graphics_companion/
31. Git and GitHub Source: https://github.com/logos
32. Git and GitHub Source: https://github.com/trafforddatalab
33. Thank you! @trafforddatalab