Some files and scripts needed for analyzing Always Sunny
The purpose of this pet project is to see if there are any patterns in the data I personally extracted from each episode of Always Sunny in Philadelphia, specifically: what makes a good episode? Data is tragically underutilized in the art world. While watching the show I noticed that the writers seemed to emphasize the fact that the core group splits up in different ways, and that in some episodes there seem to be a clear "winner." Ultimately this sort of "character grouping" analysis is applicable to all episodic, character-driven TV-shows.
I started with this data coded by hand for fun and converted everything (again by hand but not as fun) to both episode production codes and episode codes used by imdb.
Then I turned that data into a dictionary of matrices to represent which character grouped with who and whether or not that team "won" for each episode using this script. I tried running it on a simple neural net with IMDB ratings for the label data just to see what happened (nothing useful).
I wanted to make some Tableau viz's of this but I couldn't think of a good way to convert my data into a MySQL database. Fortunately I found Simba's Mongo->SQL->Tableau conversion drivers. I consolidated my raw data and imdb ratings in to a mongo database with this script.
So far the most interesting thing all this work has produced is this image I made in Tableau that shows what groups made for the best episodes.