Take a break from all your worries by looking at this visualisation showing average IMDb ratings of Cheers episodes! (made for desktop)
As I used Tableau, I could add a few details for fun into some of the episodes – to indicate certain characters’ first episodes, and when certain guest characters show up. I also threw in a few quotes from some of the episodes.
- IMDb ratings come from their datasets page.
- Episode names are from the Cheers Wikipedia episode guide.
- The quotes came mainly from the IMDb pages for each episode, but a couple came from old-fashioned Googling.
- I got the details on first appearances from the excellent Cheers Fandom wiki.
One point of note was how to make the averages for the seasons. Should you simply take an average of averages, or should you take the number of votes into account?
I thought the former was the right way, since the episodes themselves are the units of comparison. In other cases it would be different. E.g, if it was a chart of average 5k run times per month, I’d take the number of runs into account. If you did 10 runs in one month, and took 20 mins on average, but only 1 run in February, but you weren’t feeling well and took 40 minutes, the average of averages would be 30 minutes, which doesn’t represent your performance.
But in this case, I feel that more votes just means that episodes score is more robust, and doesn’t reflect the quality of the episode itself (in general, first and last episodes on IMDb seem to get the highest vote counts).
Rebecca or Diane?
As you see, the IMDb ratings don’t resolve this decades-old debate – Diane technically wins, but by a nose – there’s only 0.04 in it!
This was inspired by Dr. Birko-Katarina Ruzicka who made one in R showing average ratings of Star Trek Voyager, which I saw in this Tweet:
Dr. Ruzicka was inspired by Cédric Schrerer via the below Tweet – he made one about the US version of The Office:
And also Ansgar Wolsing via this Tweet – he did 24:
Maybe you will continue the chain?