This project entails the analysis of a dataset encompassing details on the top 10,000 manga and anime, extracted from the well-known website MyAnimeList. For further details, please refer to the GitHub repository linked here.

Anime & Manga Dataset Analysis

Overview

This project involves analyzing a dataset containing information on the top 10,000 manga and anime sourced from the popular website MyAnimeList. The dataset was crawled on January 6, 2024.

Files

• anime.csv: Contains details on the top 10,000 anime entries.
• manga.csv: Contains details on the top 10,000 manga entries.

Data Fields

Both datasets include various fields such as Title, Score, Vote, Ranked, Popularity, and more.

Step 1: Data Exploration and Understanding

1.1 Load the Data

• Loaded anime.csv and manga.csv files into Python using Pandas.

1.2 Examine the Structure

• Checked the first few rows of each dataset to understand the structure.
• Explored data types, missing values, and general statistics.

1.3 Understand the Variables

• Reviewed the data fields in both datasets to understand the meaning of each variable.

1.4 Initial Summary

• Provided a brief summary of key statistics for important variables.

1.5 Explore Unique Values

• Identified unique values in categorical variables to understand the range of categories.

1.6 Data Cleaning

• Handled missing or inconsistent data.
• Replaced ‘Unknown’ values with NaN.
• Cleaned up ‘Episodes’, ‘Duration’, ‘Members’, ‘Favorite’, ‘Volumes’, ‘Chapters’.
• Documented decisions and actions.

Step 2: Preliminary Analysis

2.1 Top Rated Entries

• Identified the top-rated anime and manga based on user scores.

2.3 Popularity Insights

• Analyzed the relationship between popularity rank and user scores.

2.4 Source Material Influence

• Investigated the success of anime adaptations based on the source material.

Step 3: Genre and Theme Analysis

3.1 Genre Distribution

• Explored the distribution of genres in manga.
• Cleaned up genre data by removing unwanted characters.

3.2 Common Themes

• Identified common themes explored in manga.

Step 4: Production Insights

4.1 Studios and Producers

• Identified the top 10 most prolific animation studios.
• Identified the top 10 most prolific production companies.

4.3 Manga Serialization Impact

• Explored the impact of manga serialization platforms on manga success.

Conclusion

This analysis provided insights into the world of manga and anime, exploring top-rated entries, popularity trends, source material impact, genre and theme distributions, and production insights. The cleaning and exploration processes were conducted to ensure meaningful and accurate analysis.

Author

• Mohammed Mebarek Mecheter
• Contact: mohammedmecheter@gmail.com
• LinkedIn: Mohammed Mebarek Mecheter
• GitHub: Mohammed Mebarek Mecheter

Feel free to contact me for any questions or additional information about this project.