We try to do a few simple things with the plotly package in order to figure out how it works.
We try to find out if voters in Germany became more impulsive over time.
Using concepts like dot-dot-dot and curly-curly we create functions that are more versatile and can be used in multiple settings.
We take a look at the differences between position = 'stack' and position = position_stack().
We talk about how to easily create labels for an aesthetic.
This is the beginning of a series about a few ggplot2 tricks I picked up along the way. In this first installment we talk about how logarithmizing scales can be beneficial.
I recreate a simulation study on the influence of luck on success compared to the influence of skill.
For my first post I create an animation using the animate package.