I learned R before the tidyverse (shout out to @BaumerBen’s Multiple Regression class Fall 2016) and have failed to update my skills. There, I said it. I’m a statistics PhD student whose code is riddled with dollar signs (pull Sara!) and the occassional loop that I’ve never wrangled into a proper apply statement (which should now be switched to purrr?). And although I have picked up some ggplot2 and dplyr (I’m not THAT much of an R hermit), I really don’t know what new functionality is available. This prevents my code from keeping up with the times. It has always been on my to-do list to work through the tidyverse documentation so that I can start using the packages in my own work, but I’ve always prioritized “done” over “pretty”.
But no longer! My plan of attack is to start blogging about my tidyverse immersion, one package at a time. Each week(ish) I will read up on a tidyverse package and ideally, update some gross code from one of my current or previous projects, showing the before and after. Maybe I’ll aim to post on Monday’s… #MakeoverMonday anyone?
What do I need to master?
That is a lot of weeks! So why am I doing this now?
Hadley Wickham gave a talk in our department recently, and I was one of the lucky five to have lunch with him beforehand. He mentioned that failing to update one’s R skills is like never updating R and RStudio versions (I’m occasionally guilty on this front as well, but let’s deal with one character flaw at a time).
When I was trying to help students at UC Berkeley’s third annual DataFest, I realized the students didn’t know what I was talking about when I was describing how I would approach a coding problem. I needed a tidyverse translator!
If not now, when?
So stay tuned, and hold me accountable.
Advice? Solidarity? Let me know! (@sastoudt)
Special thanks to @dpseidel for giving me feedback while I was drafting this post (and telling me to pull not select instead of $, see I’m learning already!).