How to crop an image to a circle in R with {cropcircles}
I hadn’t found a super-easy-you-don’t-have-to-think-about-it way to crop an image to a circle in R with a transparent background. There’s […]
Survivor Confessionals Data: Dataset showcase for {survivoR}
Confessionals loosely represent a player’s screen time where they talk strategy and replay events. It is an imperfect measure but […]
How to use multiple colour scales in ggplot with {ggnewscale}
For week 23 of Tidy Tuesday the chart I wanted to make required two colour scales. For context the dataset […]
Survivor Advantages: Dataset showcase for {survivoR}
Advantages were introduced to Survivor to give players an edge and to shake up the strategy. A successful play can […]
Survivor Do or Die: Should you sit out or fight for immunity?
Simulation analysis in R to determine the odds of success behind the Do or Die twist in Survivor
survivoR v1.0 is now on CRAN
I’m happy to announce that survivoR v1.0 is now on CRAN. The package now contains all the features intended for […]
Racial Bias in Survivor: Are People of Colour Disproportionately Voted Out First?
After episode 9 of season 42 of Survivor, there was a lot of discussion of implicit racial bias in Survivor. […]
How Unbalanced is the Editing on Australian Survivor: Blood vs Water Compared to the US?
If you’ve been watching Australian Survivor Blood vs Water you will have noticed a handful of people getting a lot […]
survivoR now on CRAN!
I am pleased to announce survivoR 0.9.2 is now on CRAN. The survivoR data package is a collection of datasets […]
survivoR | Data from the TV series in R
596 episodes. 40 seasons. 1 package! I’m a pretty big fan of Survivor and have religiously watched every season since […]
Don’t get fooled by the Gambler’s Fallacy
A while ago I simulated Martingale strategies and some variations. This is the strategy where you double your bet on […]
Evolve new colour palettes in R with evoPalette
What’s that saying? Choice is the enemy of happiness, or something like that. There are so many colour palettes out […]
Some basics and intuition behind GAN’s in R and Python
Generative Adversarial Networks are great for generating something from essentially nothing and there are some interesting uses for them. Most […]
Simulating data with Bayesian networks
Bayesian networks are really useful for many applications and one of those is to simulate new data. Bayes nets represent […]
Use more of your data with matrix factorisation
Previously I posted on how to apply gradient descent on linear regression as an example. With that as background it’s […]
