Potpourri: Statistics #60

Mining Social Media (also a good introduction to Python)
All The Economist Graphic Detail visualizations in one convenient PDF
R Cookbook, 2nd Edition
How to use Test Driven Development in a Data Science Workflow
Why are polls from different pollsters so different?
Difference-in-Differences
The list of 2019 visualization lists
– Emil Hvitfeldt’s Package Calendar: 1) datalegreyar, 2) glue, 3) details, 4) carbonate, 5) ymlthis, 6) skimr, 7) gghalves, 8) globe4r, 9) gapminder, 10) reactable, 11) slide, 12) polite, 13) gtrendsR, 14) networkdata, 15) covr, 16) Sparkline, 17) golem, 18) flexdashboard, 19) ggtext, 20) rayrender, 21) devout, 22) highcharter, 23) precommit, 24) styler
Introducing sortable to add drag-and-drop to your shiny apps
You can replicate almost any plot with R
Simulation-based Power Calculations for Conjoint Experiments
Mastering Spark with R
10 Tricks for tidyverse in R
Shiny Apps: Development and Deployment
How to Clean Messy Data in R
10 Levels of ggplot2: From Basic to Beautiful
What They Forgot to Teach You About R