A repository for my contributions to the r4ds Tidy Tuesday intiative: https://github.com/rfordatascience/tidytuesday
A plot of the strength of various categories of common password, labelling those were especially easy or difficuly to crack.
A column chart (using polar coordinates) describing the features of songs from popular spotify artists.
An animation showing the the weekly attendances at NFL games for 2 teams that moved to LA at a similar time.
A map, and column chart showing salaries and fees of US universities.
Partial pooling linear model (using the lme4 package) to see how IMDB ratings of The Office (US) varied within and between seasons.
Number of goals scored by each team in the knock-out stages of the women's world cup.
The proportion of cats and dogs in RSPCA Australia (QLD and NSW) care, that have been rehomed.
The price and metacritic scores of videogames downloaded from Steam, using a GameBoy theme.
Electricity generation in Europe from 2016 - 2018. A multi-facetted patchwork plot, showing powergeneration by country, by technology, and by year.
Comparison of datasets with similar summary statistics, that differ in appearnce - to highlight the importance of plotting data.
World record times on various Mario Kart 64 tracks.
Traits of various dog breeds.