R workflow – tidyverse first

While working recently on some of my data projects and talking to colleagues I have realized, that my style of R programming has changed significantly. Now, I almost always use tidyverse packages and have fully embraced the workflow these packages encourage. Particularly, pipes (%>%) and dplyr idioms are hardwired into my R workflow.

For me, the tidyverse is a major innovation and I have followed its evolution closely. It makes it more easy to transform data and scripts are easier to understand. In fact, I have moved from using Base R only, over using the plyr package a lot, to the tidyverse as a new R dialect.

I fully support the “tidyverse first” approach. Having taught R to various social science students over the years, I realized that the tidyverse allows R beginners to work with a particular R dialect that hides many of the programming concepts that are difficult to grasp at the beginning. The tidyverse allows users to focus on data analysis.

R snippets on Github for Party Facts and the recently added ParlGov Snippets provide examples of my usage of the tidyverse.

Learning

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