survivoR 2.1.0 is now available
Good news everyone! survivoR 2.1.0 is now available. The most exciting feature of this release is the new confessional timing app.
Category: R
Alone Australia is now included in {alone}
Alone Australia is now included in the {alone} R package as well as the cast of season 10 of the US version.
Alone R package: Datasets from the survival TV series
I have been watching the survival TV series ‘Alone,’ where 10 survivalists are dropped in an extremely remote area and […]
Select colours from an image in R with {eyedroppeR}
There are fancy ways to extract colours from images but sometimes it’s easier if you could simply click on the […]
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 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 […]
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 […]
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 […]
