Mara Averick Jul 20, 2023
Andrew Heiss 

Wrote up some debugging advice for my #dataviz students and figured it's useful for everyone: **Slow down, simplify, and do small things**

https://datavizs23.classes.andrewheiss.com/news/2023-07-05_messy-broken-code-tips.html

It includes a quick example of how to incrementally fix a broken #rstats ggplot

Data Visualization with R - Tips for debugging and cleaning broken code

Jul 19, 2023 at 5:04pmWeb
Show threadGregJul 19, 2023
@andrew Great advice for bug fixes and development in general too. If you merge and deploy everything at the same time and it doesn't work, it makes it much harder to identify the culprit and fix it.
Show threadJordi RosellJul 19, 2023
@andrew beautiful. I usually organize teaching in tha same way. Coping the entire code again and adding one line, so I only explain what that line so to the the pipe (%>% pipe or + pipe) 👍
Show threadJordi RosellJul 19, 2023
@andrew at the end I recommend them to write the comple pipa as a function
Show threadAndrew Heiss Jul 19, 2023
@jrosell I also show them how to select up to the next %>% or + and then inspect it up to that point when they have a preexisting pipeline https://datavizs23.classes.andrewheiss.com/news/2023-07-05_messy-broken-code-tips.html#run-the-code-incrementally
Data Visualization with R - Tips for debugging and cleaning broken code

Show threadJordi RosellJul 19, 2023
@andrew I understand. On Google Colab I use a "cell based" approach https://colab.research.google.com/drive/1RbN5o-rMioUT8TCWiEDs7rF-cJft2tux
Google Colaboratory

Show threadHao YeJul 20, 2023
@andrew Always appreciate a debugging reference!