Anime Data Analysis and Visualisation

5 min readJul 28, 2023

In this article, I will walk you through the findings of my anime data analysis project, which involved using SQL for analysis and Tableau for visualisation.

Introduction

Anime has recently captivated the world, and I’ve been interested in analysing this field for a while. A website called ‘MyAnimeList’ compiles a vast anime database, allowing users to rate their favorite shows. This dataset holds valuable insights, such as the total number of anime in the data, the different types of anime, anime genres by count, overall user rating distribution, most popular anime, highest rated anime, favourite genre for veteran viewers (at least 50 watched) and the favourite genre for newbie viewers. Understanding viewer preferences can help guide the future direction of this rapidly growing industry.

The data used for this analysis was obtained from Kaggle. It consists of user ratings for different anime shows they have watched. The ratings are given on a scale of 1 to 10.

Two files were used in this analysis:

1. Anime.csv:
— anime_id: A unique identifier for each anime.
— name: The title of the anime.
— genre: The genre(s) associated with the anime.
— type: The format in which the anime was aired (e.g., TV series, movie, OVA, ONA, special).
— episodes: The number of episodes in the anime (1 for movies).
— rating: The average user rating out of 10 for each anime, as provided by the website.
— members: The number of community members following each anime.

2. Rating.csv:
— user_id: A unique identifier for each user.
— anime_id: A unique identifier for each anime entry.
— rating: The user’s rating is out of 10 for the respective anime. A rating of -1 indicates that the user watched the anime but did not provide a rating.

To view my complete project I will also link my GitHub.

What is the total count of the animes in the dataset?

There are 12,294 animes that will be covered in the dataset. This was important to know as it provides the overall scope of the data, defines the boundaries of our analysis, and adds context to the findings.

What are the different types of anime and their distribution in the dataset?

There are 6 different types of anime present excluding the blanks in the dataset. The 3 types that were most prevalent were TV shows, OVAs, and movies.

What are the different types of genres and their distribution in the dataset?

There were 40 different genres however the screenshot shows the top 11. Unsurprisingly the top 2 were comedy and action. At first, I was surprised to see that the fantasy genre has a low count, however, the dataset that I'm exploring was compiled together 7 years ago. The fantasy genre would be within the top 5 genres if a more recent dataset was used.

What are the rating statistics?

The average rating was found to be 6.47, the minimum rating was 1.67 and the maximum rating was 10.

What was the most popular anime?

The anime with the most members and therefore most popular was found to be death note!

What was the highest-rated anime?

The anime titled ‘Taka no Tsume 8: Yoshida-kun no X-Files’ emerged as the highest-rated anime in the dataset, securing a perfect rating of 10. However, it is essential to note that this exceptional rating was based on feedback from only 13 members. With such a small sample size, individual ratings carry more weight, and the presence of a single rating of 10 significantly influenced the overall average. In larger datasets with more ratings, extreme values have less impact, making the ratings more representative of the general audience’s opinions. Hence, the unique distinction of this anime’s perfect rating can be attributed to the limited number of members who contributed to its score.

What are the most watched genres for newbie watchers (less than 50 watched)?

Besides the blanks, the top 3 genres are action, comedy, and adventure.

What are the most watched genres for veteran watchers (at least 50 watched)?

The top 3 genres for veterans are once again action, comedy, and adventure. However, the gap between action and comedy for veteran watchers is very minimal. Personally, this makes sense as sometimes comedy in anime is an acquired taste, as it seems absurd and ridiculous at first glance.