I found a dataset on Kaggle that detailed the overall and episode-specific IMDB ratings of the 250 highest rated TV shows.
This is a snapshot of the joined data sorted descendingly by the average of the TV show’s average episode rating, and its overall rating.
Below is the distribution of the number of seasons in a TV show.
I grouped the list by the number of seasons to see how the average rating of TV shows changes with the number of seasons in a show.
These are the TV shows with 3 or more seasons listed descendingly by the average of the TV show’s average episode rating, and its overall rating.
Interestingly, there is only a weak correlation (0.337) between a TV show’s average rating, and its overall rating.
Taking into account all the ~250 shows, the below plot shows how the average ratings of episodes vary over seasons. It seems that ratings generally decline over seasons.
These are the highest rated episodes among all the TV shows.
Accounting all TV shows, these are the seasons with the highest average episode ratings.
I have uploaded the Python notebook, within which I conducted my analyses, and the data on my GitHub.
Subscribe to my mailing list to be notified about my posts: