50 ways to show your data
summary
Shows reproducible R code using ggplot2 and tidyverse to turn messy tables into tidy data, including converting a scraped Formula One 2016 dataset to long format and faceting for per-driver trends. Demonstrates specific packages: waterfalls (fixed after a bug report), geom_parliament/ggpol, treemap, corrplot variants, radar charts, marginal histograms, jitter/repel for overplotting and labels, animated Gapminder-style plots, maps using Google API with live parking data, and exportable scripts that reproduce every example.
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chapters (22)
- 0:00Welcome
- 1:45R and Tidyverse overview
- 3:10RStudio setup and demo files
- 13:07Cleaning F1 race data
- 16:23Line plot of race points
- 18:11Faceting driver performance
- 19:36Box plots for stats
- 22:31Violin plots for points
- 24:02Lollipop charts for cars
- 25:51Encircling data points
- 27:17Addressing overplotting in scatter plots
- 29:55Repel data labels
- 31:20German election results
- 33:51Tree maps of phone data
- 35:59Fixing waterfall charts
- 38:28Heatmaps and bubble correlations
- 41:42Marginal plots for scatter
- 43:11Radar charts for cars
- 44:40Parking garage maps
- 46:48Animated economic graphs
- 53:34Adding interactivity
- 58:10Summary
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