Potpourri: Statistics #57

Keep It Together: Using the tidyverse for machine learning
Learn to purrr
Mastering Shiny
A Comprehensive List of Handy R Packages
The challenges of using machine learning to identify gender in images
How is polling done around the world?
How to Get Better at Embracing Unknowns
Drawing maps in R
Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
Visualizing Locke and Mill: a tidytext analysis
Tutorial: Cleaning UK Office for National Statistics data in R
– Transitioning into the tidyverse: part 1, part 2
Your Friendly Guide to Colors in Data Visualisation
Optimising your R code – a guided example
Learning data visualization
Reference Collection to push back against “Common Statistical Myths”
mutate_all(), select_if(), summarise_at()… what’s the deal with scoped verbs?!
Tools for Exploring and Comparing Data Frames
Tom’s Cookbook for Better Viz
Themes to Improve Your ggplot Figures
Lesser Known R Features
What Statistics Can and Can’t Tell Us About Ourselves
A Graphical Introduction to tidyr’s pivot_*()
n() cool #dplyr things
Bayesian Linear Mixed Models: Random Intercepts, Slopes, and Missing Data
Prepping data for #rstats #tidyverse and a priori planning
NYT-style urban heat island maps