My prior post on tidyverse split-apply-combined ended with me favouring split + map_dfr as a replacement for group_by + do. In this post I look at some idioscrasies of the split function from Base R.

My prior post on tidyverse split-apply-combined ended with me favouring split + map_dfr as a replacement for group_by + do. In this post I benchmark the runtime of base R split().

I currently process a lot of data a single entity at a time, but have a data.frame representing multiple entities as input.

Sometimes it doesn’t feel like a project (no matter how small!) is completed until there’s a package for it.

Note: for keen followers, this is a rehash of my hack that was the pipify package.

I often need to create complicated plots within a function.

While convex hulls can produce some interesting results (See parts 1, 2, 3, 4 ) they’re expensive to compute relative to just drawing lines.

As mentioned previously ( 1, 2, 3 ) I’m attempting to use chull() to create some stuff.

As mentioned yesterday, I’m using chull() to create some stuff.

As mentioned yesterday, I’m using chull() to create some stuff.