Personal IMDB Calendar Heatmaps
In the previous post I changed the reading challenge personal folder to a submodule, so that I can use the personal repository for another project: This one. A Python script is processing the IMDB Rating export and generates calendar heatmaps similar to the GitHub contribution activity plots.
The first version used the dayplot Python library, but this doesn't allow per-cell categorical colors. So I asked Claude to change the code to pure matplotlib.
In the IMDB Ratings every entry has a Type, I chose to color them differently. But first I merged the Types like this:
And I removed "Video" and "Video Game". Both are rare in my data. And especially for Video Game the date of rating has nothing to do with the date I actually played the game.
As a result we get these Types, and they get colors when mixed have visible differences:
"Movie": "#16a34a", # green "TV Episode": "#4f46e5", # indigo "TV Series": "#ea580c", # orange "Short": "#0d9488", # teal
The code would be much shorter without any Type colors, like the green in the GitHub contribution calendar heatmaps.
The full source code is mirrored on GitHub.
A few times in the past, I rated a large number of TV episodes in a single day. The highest count was 140. Obviously, I didn’t actually watch that many episodes on that day. So the data is not perfect for this kind of plot. Still the resulting images are a good indicator how much I watched Movies or TV Episodes.
Next are some example years from my data. In the first years I used IMDB (2004 till 2010) I only rated Movies. I don't know anymore why I started to rate TV Episodes in 2010. But since then I use IMDB ratings to track what I have already watched.
My ratings plot for 2010, the year I started to rate TV Episodes:

I can see in the plots the years where a lot happened and I had no time to watch Movies or Series, for example 2015:

And there is the obvious year where we all spent time at home and watched Movies and Series, 2020:

Overall a good way to visualize my personal Movie and TV Series consumption.