Appreciating the Beauty of dplyr


Hadley Wickham has once again1 made R ridiculously better. Not only is dplyr incredibly fast, but the new syntax allows for some really complex operations to be expressed in a ridiculously beautiful way.

Consider a data set, course, with a student identifier, sid, a course identifier, courseno, a quarter, quarter, and a grade on a scale of 0 to 4, gpa. What if I wanted to know the number of a courses a student has failed over the entire year, as defined by having an overall grade of less than a 1.0?

In dplyr:

course %.% 
group_by(sid, courseno) %.%
summarise(gpa = mean(gpa)) %.%
filter(gpa <= 1.0) %.%
summarise(fails = n())

I refuse to even sully this post with the way I would have solved this problem in the past.

  1. Seriously, how many of the packages he has managed/written are indispensable to using R today? It is no exaggeration to say that the world would have many more Stata, SPSS, and SAS users if not for Hadleyverse. 

This entry was tagged as rstats dplyr hadleyverse

blog comments powered by Disqus