Anime Dataset & Recommendation Tool

A collection of anime data from MyAnimeList and AniList, updated daily. This project also includes a script to recommend anime based on shared genres and tags.

Features

• Daily Updates: Runs automatically every day at midnight UTC.
• Data Sources: Collects data from AniList and MyAnimeList.
• Recommendation Tool: A terminal script that finds similar anime by comparing genres and tags.
• Data Validation: A script to check for missing data or gaps in the dataset.

Project Structure

├── data/
│   └── raw/               # CSV files containing the anime data
├── docs/                  # Documentation
├── src/
│   ├── anilist_api.py     # Script to get data from AniList
│   ├── jikan_api.py       # Script to get data from Jikan (MyAnimeList)
│   ├── mal_api.py         # Script to get data from official MyAnimeList API
│   ├── recommend_anime.py # Script to recommend anime
│   └── check_missing.py   # Script to check data coverage
└── requirements.txt       # List of Python dependencies

Installation

1. Clone the repository

   git clone https://github.com/LeoRigasaki/Anime-dataset.git
   cd Anime-dataset

2. Install dependencies

   pip install -r requirements.txt

   Requires Python 3.11 or higher.

Usage

Recommendation Tool

To find similar anime:

python src/recommend_anime.py

Follow the prompts to search for an anime and see a list of similar titles.

Data Collection

To run the data collection scripts manually:

From AniList:

python src/anilist_api.py

From Jikan (MyAnimeList):

python src/jikan_api.py

Check Data

To generate a report on the dataset:

python src/check_missing.py

This creates a report at data/missing_data_report.txt.

Data Format

The data is saved as CSV files in the data/raw/ directory. Main columns include:

• anime_id: Unique ID
• title: Title of the anime
• score: Average score
• genres: List of genres
• tags: List of tags (from AniList)
• members: Number of users tracking the anime
• synopsis: Description

Automation

The scripts are set to run automatically using GitHub Actions. You can check the Actions tab for the status of the daily updates.