News and Notes from PolicyViz - Issue #10
News and Notes from PolicyViz - Issue #10
Hi Subscribers,
Thanks for your continued support of PolicyViz! My apologies for missing the last newsletter--between a crucial error on the website, prepping for a new class, and a bunch of other things, I just didn't get to it.
I've got something special posting later today (Monday, February 7th)--a long (maybe too long?) post on diverging color palettes. I think far too many use diverging palettes as an incorrect substitute for sequential color palettes. More generally, I think we all need to be clear and obvious about labeling the midpoint of our diverging color palettes. It doesn't matter if the midpoint is zero or an average or an index value or the median, as long as it's clearly marked and described, the reader/user will know from which value the scale is diverging!
You may have also seen through my Twitter feed and on my YouTube channel that I've started using (and documenting) my Tableau learning journey. I've tinkered on the edges of Tableau for quite some time and I felt the new year was a good chance to just dive into it. Plus, I'm hopeful I can learn enough that I can teach some of my Urban Institute colleagues on how to use the tool.
Having said that, there are some aspects of Tableau that I just don't quite get. Why can't you see all of your data all the time? Even the calculated fields? Why do you need to take an extra step to add a column header to a table with just one set of values? It makes no sense and it's pretty infuriating!
I'm sure more seasoned Tableau learners have forgotten or gotten over these seemingly small things, but I try to think of the small organization or nonprofit of 6, 8, or 12 people just trying to be better with their data. Do these barriers to using the tool more easily and quickly stop them from fully embracing the tool? Does it turn them off to visualizing their data altogether? I hope not. And hopefully my continued experiences as a beginner can help them and others.
If there are aspects of Tableau or data visualization more generally that I can be helpful with, please reach out and let me know!
Thanks and take care,
Jon
Podcast Episode #211: Jock Mackinlay
Jock D. Mackinlay is the first Technical Fellow at Tableau Software. He believes that well-designed software can help a wide-range of individuals and organizations work effectively with data, which will improve the world. He is an expert in visual analytics and human-computer interaction who joined Tableau in 2004 after being on the PhD dissertation committee of Chris Stolte, one of the cofounders of Tableau. Jock visits the show--posting tomorrow!--to talk about his work and his vision of the future for data visualization tools.
Podcast Episode #210: Dr. Tyler Morgan-Wall
Dr. Tyler Morgan-Wall is the developer of the mapping and data visualization package rayshader along with the raytracing package rayrender and several other R packages (the rayverse). He is a passionate advocate for 3D data visualization, open source software, and reproducible workflows in dataviz and data science. He has a PhD in Physics from Johns Hopkins University and works as a researcher at the Institute for Defense Analyses in Washington DC.
What I'm Reading
Books
The Other Black Girl: A Novel, by Zakiya Dalila Harris
Protecting Your Privacy in a Data-Driven World, by Claire Bowen
Atlas of the Invisible: Maps and Graphics That Will Change How You See the World, by James Cheshire and Oliver Uberti
Making Numbers Count, by Chip Heath and Karla Starr
Articles
Fooled by beautiful data: Visualization aesthetics bias trust in science, news, and social media, by Chujun Lin and Mark Allen Thornton
Special Issue on Measuring LGBT Populations, Nancy Bates, Stephanie Steinmetz, and Mirjam Fischer
Note: As an Amazon Associate I earn from qualifying purchases.