{ggiraph}
It is really simple to turn a ggplot into an interactive visualization. In this blog post you’ll learn how to do that with {ggiraph}. Also we’ll explore ways to enhance the interactivity with Shiny.
Bar charts are easy to make but hard to perfect. Let’s create a small checklist to make things easier.
We take a look at a couple alternatives to paired bar charts.
We explore alternatives for heat maps to take sample sizes into account.
We explore alternative correlation matrix plots.
This blog post is a quick one. It highlights a few hidden gems (functions) from well-known or not so well-known packages.
We build rebuild a ‘Storytelling with Data’ plot which uses rounded rectangles. I’ll show you an easy and a hard way to make rectangles round.
We try to imitate the Storytelling with Data look with ggplot
Functional programming is a mighty sword. Today, we use it to avoid tedious repetitions when things go wrong in ggplot.
This is a short tutorial on how to import fonts and icons in R using the showtext package.
Inspired by a datawrapper blogpost, we explore how to work with fewer colors in ggplot.
I advocate to take part in the TidyTuesday events to learn with and from others.
The ggplot2-tips series is continued with a few example plots from the ggforce package
The patchwork and ggforce packages can be used to compose plots from multiple subplots. Let’s have a look at how that works.
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.