license: mit
task_categories:
- text-generation
- text2text-generation
language:
- en
tags:
- Anime
- Dataset
pretty_name: Anime
Anime Dataset
Overview
This dataset contains detailed information about various anime series, including their genre, setting, protagonist demographics, themes, and ratings. The dataset is designed to provide a diverse collection of anime, capturing different genres, settings, and protagonist characteristics.
Dataset Details
The dataset includes the following fields:
- Title: The title of the anime.
- Genre: The primary genre of the anime.
- Subgenres: Additional subgenres that describe the anime.
- Setting: The primary setting where the anime takes place.
- Protagonist_Demographics: Demographic information about the main protagonist.
- Protagonist_Gender: The gender of the main protagonist.
- Protagonist_Ethnicity: The ethnicity of the main protagonist.
- Main_Studio: The animation studio that produced the anime.
- Theme1: Key themes explored in the anime.
- Theme2:2nd Theme of anime.
- Number_of_Episodes: The total number of episodes in the series.
- Rating: The average rating of the anime.
Sample Data
Below is a snippet of the dataset to give you an idea of its structure:
Title,Genre,Subgenres,Setting,Protagonist_Demographics,Protagonist_Gender,Protagonist_Ethnicity,Main_Studio,Theme1,Theme2,Number_of_Episodes,Rating
Hakugei: Legend of Moby Dick,Adventure,Sci-Fi,Space,Adult,Male,Multi-Ethnic,Madhouse,Whaling,Space,26,7.1
Casshern Sins,Action,Sci-Fi,Post-Apocalyptic,Adult,Male,Fictional,Madhouse,Robots,Survival,24,7.9
Shigurui: Death Frenzy,Action,Historical,Edo Period Japan,Adult,Male,Japanese,Madhouse,Swords,Brutality,12,7.6
Kaiba,Sci-Fi,Romance,Futuristic,Adult,Male,Fictional,Madhouse,Identity,Memory,12,8.1
Rainbow: Nisha Rokubou no Shichinin,Drama,Action,Post-WWII Japan,Teen,Male,Japanese,Madhouse,Friendship,Survival,26,8.2
Usage
This dataset can be used for various purposes, including but not limited to:
Data Analysis: Analyzing trends and patterns in anime genres, themes, and ratings.
Machine Learning: Training models to predict anime ratings or recommend similar shows.
Research: Studying the representation of different demographics and themes in anime.
Entertainment: Discovering new anime to watch based on various attributes.
Contributing
If you have suggestions or improvements for this dataset, feel free to contribute by opening an issue or submitting a pull request.