Unhappy Endings
By: Callum Ballard
Tags: Data Science, Python, Game of Thrones, Data Visualization, TV Series

Let’s take our dataset for a test drive by first looking at something very simple. In our database of ‘finished’ TV shows, which ones have the highest overall series rating?

Even if its ending did sour things, Game of Thrones still enjoys a healthy series rating of 9.4, surrounded by the kind of shows you’d expect to see at the top of such a ranking (Breaking Bad, The Wire, and The Sopranos), as well as some you may not have even heard of (Leyla and Mecnun is a Turkish dramady currently available on Netflix, whilst Avatar, Death Note, and Fullmetal Alchemist are all Japanese animé).

Let’s go deeper on the top five series and track the individual episode ratings of each show’s run.

The first thing that jumps out, as we might expect, is the precipitous fall in ratings at the end of Game of Thrones. We should also note that this drop was not inevitable — there are plenty of examples of high quality shows not fluffing their lines at the very last. Indeed, the other shows here pretty much hit their respective peaks during their final episodes (with The Sopranos’ slight downtick perhaps caused by its infamous ‘cut to black’ ending).

The other less obvious thing that presents itself here is the relationship between the overall series rating (as defined in the original dataset) and the average of the episode ratings. We would expect these to be very similar, if not identical, though this doesn’t seem to be the case. For example, The Wire’s episode ratings, though consistently high, still average out at a whole point less than its overall series rating (8.25 vs 9.30, respectively).

Indeed if we compare these two measures for the whole dataset, we see that the correlation between series ratings and average episode ratings is actually quite weak.

The purple line here represents x = y. Very few titles sit on (or indeed especially near) it

Weirdly, we see that six out of the seven shows with the biggest discrepancies between overall series and episode ratings are animations, and five of these are Japanese Animé (Naruto, Cowboy Bebop, Death Note, and two helpings of Dragon Ball Z).

Looking at the episode trackers of the shows with the largest discrepancies, we see high standard deviations (and in the case of Batman and Dragon Ball Z, rather inconsistent quality on an episode by episode basis).

We can conjecture that there’s a certain ‘nostalgia factor’ at play here — people might have fond ‘overall’ memories of a show that aired more than a decade ago, which would result in high ratings for the series as a whole.

However, time might have erased memories of dud episodes, which then get lower individual episode ratings (we can assume that people rating on an episode-by-episode basis are more likely to have watched them recently with a more objective eye).

The data does bear this out to an extent. There is a negative correlation between a show’s end year, and the discrepancy between its overall series rating and average episode ratings.

The further towards the top of the chart a title is, the higher its series rating is compared to the average rating of its individual episodes. Older shows are likelier to have such discrepancies.

So, given we’ve seen inconsistent series with high variance in episode ratings, which shows manage to keep up a consistent quality throughout their entire runs? We can answer this question by plotting a show’s episode ratings’ mean against its standard deviation.