Apart from mentioning it, I will not talk much about the TidyVerse ecosystem of opinionated packages much in this tutorial. For our introduction to data cleaning with R we we will focus on using features of the data.table package
But stringr, lubridate, ggplot2... those are all part of the tidyverse! Which is great, these days I think the tidyverse is the main thing R has got going for it. Cool to see that there is a steemRdata package.
One thing that I think is a BIG PROBLEM with R is how namespaces are handled. Even though you don't have to do steemRdata::getDelegation, you should so:
- readers know which
getDelegationyou are calling. For example in Python,from package import *is discouraged for this reason. - sometimes two packages will import the same function names causing the first to get masked.
Namespaces can be annoying alight, I do get conflicts with packages I have loaded.
I use lubridate and ggplot2 all the time but there are many other newer packages in this group that I want to learn more about. The TidyVerse is great.