Potpourri: Statistics #60

599. Mining Social Media (also a good introduction to Python)
600. All The Economist Graphic Detail visualizations in one convenient PDF601. R Cookbook, 2nd Edition602. How to use Test Driven Development in a Data Science Workflow603. Why are polls from different pollsters so different?604. Difference-in-Differences605. The list of 2019 visualization lists606. ~~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~~607. Introducing sortable to add drag-and-drop to your shiny apps608. ~~You can replicate almost any plot with R~~609. Simulation-based Power Calculations for Conjoint Experiments610. Mastering Spark with R611. 10 Tricks for tidyverse in R612. Shiny Apps: Development and Deployment613. How to Clean Messy Data in R614. 10 Levels of ggplot2: From Basic to Beautiful615. What They Forgot to Teach You About R