Take a sad chart and make it better

tiny.cc/ims-viz

Trang Le

University of Pennsylvania

Talk at UNC Institute of Marine Sciences

2021-08-30

Image by Tyler Morgan Wall

Rules don't always apply.

what am I trying to say

with my chart?

I would use histograms or stacked bar charts for each comparison.
Trade-off: node sizes, edges not shown.

Day 3 vs. Day 0

Day 7 vs. Day 0

Metabolome

Proteome

Transcriptome

Novel nodes

how much information
should I show?

Histograms heavily depend on bin width and location

https://twitter.com/timtriche/status/1056898767985799168

Basic statistical considerations for physiology

performance

Model B – Model A

Model B

Model A

but sometimes binning is helpful... 

e.g. to solve overcrowding problem

https://davidcarslaw.com/data/openair/openair_basic/

Graphical Presentation of Multidimensional Flow Histogram Using Hexagonal Segmentation.

Yukio Kosugi, Jun Ikebe, Nobuyuki Shitara, and Kintomo Takakura (1986).

Cytometry 7, 291-294.
 

Scatterplot matrix techniques for large N.

Carr, D.B., Littlefield, R.J., Nicholson, W.L., and Littlefield, J.S. (1987).

Journal of the American Statistical Association, 82, 424–436.

ggcyto::ggcyto() + geom_hex(bins = 64)

https://rud.is/b/2015/05/14/geojson-hexagonal-statebins-in-r/

what other ways to

reduce the cognitive burden?

  • direct labeling
  • reduce number of labels
  • highlighting
  • consistent color scheme

https://github.com/slundberg/shap

Risk of hypertension

utilize

small multiples

(facets)

facet_grid(
  cols = vars(...),
  scales = 'free', 
  space = 'free'
)

paper ≠ presentation

  • amount of information
  • annotation
  • highlights
  • abbreviations
  • builds
  • text sizes
  • ...

 

White scientists are overrepresented

scientists are underrepresented

Asian

We were not adequately powered to detect the differences in other groups.

We were not adequately powered to detect the differences in other groups.

We were not adequately powered to detect the differences in other groups.

on colors

  • sequential, quantitative, divergent
  • colorblind friendly palettes
+ scale_color_viridis_c()

trang1618/ims-viz (github.com)

+ rcolorcarto::scale_color_carto_d()

trang1618/ims-viz (github.com)

Mistakes, we have drawn a few (Sarah Leo)

Resources

Data visualization: A practical introduction (Kieran Healy)

http://www.thefunctionalart.com/ (Alberto Cairo)

https://www.reddit.com/r/dataisbeautiful/

https://viz.wtf/

Manolis Kellis on How to Present

https://karaman.is/dataviz/

https://clauswilke.com/dataviz/

http://www.datavizdoneright.com/

https://www.data-to-viz.com/caveats.html

https://medium.economist.com/why-you-sometimes-need-to-break-the-rules-in-data-viz-4d8ece284919

@spcanelon's personal collection of data visualization bookmarks from Twitter

your turn

tiny.cc/
rladies-dataviz 

Tools → Global Options → R Markdown:

uncheck Show output inline

Great data stories

https://pudding.cool/

https://www.nytimes.com/

https://flowingdata.com/

https://ourworldindata.org/

http://mkweb.bcgsc.ca/

https://flowingdata.com/2020/07/20/this-age-is-the-new-age/

windRose(openair_data)
library(treeheatr)
heat_tree(penguins, target_lab = 'species')

github.com/trang1618/treeheatr

How do you remove legend title?
What about y-axis title?

https://github.com/EmilHvitfeldt/r-color-palettes/

https://github.com/gadenbuie/ggpomological

https://github.com/hrbrmstr/hrbrthemes

https://github.com/zumbov2/colorfindr

Key principles for data visualization

By Trang Le

Made with Slides.com

Key principles for data visualization

Talk at UNC Institute of Marine Sciences 2021-08-31

  • 167
Loading comments...

More from Trang Le