This week, Hugo speaks with Angela Li, about spatial thinking in data science. Angela is the R Spatial Advocate at the Center for Spatial Data Science at U Chicago and also runs R-Ladies Chicago. They’ll be speaking about what spatial thinking means, particularly in an age when so much spatial data impacts us all, from Google maps to Uber & Lyft to public policy involving inherently spatial questions. So many questions can be framed spatially, from urban planning and transit, policy and government, to placement of ads. Spatial data is everywhere but when should we be thinking spatially and what type of tools exist to deal with these questions? Listen to find out.

LINKS FROM THE SHOW
DATAFRAMED GUEST SUGGESTIONS

• DataFramed Guest Suggestions (who do you want to hear on DataFramed?)

FROM THE INTERVIEW

• Angela on Twitter
• Angela's Website
• R Spatial Workshop Notes (By Angela Li)
• Center for Spatial Data Science
• Zen and the Art of Workflow Maintenance (Slides, By Jenny Bryan)
• Software Carpentry Geospatial Curriculum
• Tyler Morgan-Wall’s Presentation (Video)
• Data Science? Make it Spatial (Slides, By Angela Li)
• Elaine McVey’s talk at rstudio::conf (Video)
• Agile Analytics Series (By Michael Kaminsky)

FROM THE SEGMENTS

Data Science Best Practices (with Ben Skrainka ~22:48)

• On Writing Well (By William Zinsser)
• The Elements of Style (By William Strunk Jr.)
• A Guide for the Young Economist (The MIT Press) (By William Thomson)
• Crafting Your Research Future: A Guide to Successful Master's and Ph.D. Degrees in Science & Engineering (By Charles X. Ling & Qiang Yang)
• Cross-industry standard process for data mining

Statistical Distributions and their Stories (with Justin Bois ~38:40)

• Probability distributions and their stories (By Justin Bois)
• Information Theory, Inference, and Learning Algorithms (By David MacKay)

Original music and sounds by The Sticks.