Name: Manga 2024 Details With Review
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

Manga 2024 Details With Review

Manga Dataset Description

Our comprehensive Manga Dataset, sourced from MyAnimeList (MAL), includes detailed information on over 24,000 manga titles. This dataset has been meticulously cleaned to ensure accuracy and consistency, making it an invaluable resource for researchers, analysts, and enthusiasts alike. Key features of the dataset include:

Manga Titles: Includes the names of over 24,000 manga series.
Genres: Detailed genre information for each manga, allowing for genre-specific analysis.
Authors and Artists: Information about the creators behind each manga, including authors and illustrators.
Publication Dates: Data on when each manga was first published, providing historical context and trends.
Ratings: Comprehensive ratings for each manga, sourced from user reviews on MAL.
Reviews: Full reviews from users, offering qualitative insights into the reception and impact of each manga.
Popularity Metrics: Includes the number of users who have read or are reading each manga, as well as their favorites.

Potential Uses

This dataset is ideal for a wide range of applications, including but not limited to:

Trend Analysis: Identifying popular genres, studios, or trends over time.
Sentiment Analysis: Analyzing viewer reviews to gauge public sentiment and common themes in viewer feedback.
Recommendation Systems: Developing algorithms to recommend anime based on viewer preferences and ratings.
Market Research: Understanding viewer demographics and preferences to inform production and marketing strategies.
Academic Research: Studying cultural trends and influences within the anime industry.

Data Format

The dataset is available in a CSV file format, with each row representing a unique anime and each column representing a specific attribute of the anime. The structured format allows for easy integration with data analysis tools and software.

This dataset is ideal for exploring trends and patterns in manga publishing, analyzing user preferences and sentiments, and conducting various forms of data analysis and machine learning applications. Whether you're looking to understand the evolution of manga over time or identify key factors that contribute to a manga's popularity, this dataset offers a robust foundation for your research and analysis.

Tables

Manga Cleaned

@kaggle.ddmasterdon_manga_2023_details_with_review.manga_cleaned

26.81 MB
71,357 rows
26 columns

CREATE TABLE manga_cleaned (
  "synopsis" VARCHAR,
  "background" VARCHAR,
  "serialization" VARCHAR,
  "authors" VARCHAR,
  "pictures" VARCHAR,
  "status" VARCHAR,
  "updated_at" TIMESTAMP,
  "popularity" BIGINT,
  "related_manga" VARCHAR,
  "num_chapters" BIGINT,
  "media_type" VARCHAR,
  "nsfw" VARCHAR,
  "main_picture" VARCHAR,
  "title" VARCHAR,
  "end_date" VARCHAR,
  "genres" VARCHAR,
  "num_scoring_users" BIGINT,
  "id" BIGINT,
  "mean" DOUBLE,
  "num_volumes" BIGINT,
  "rank" DOUBLE,
  "start_date" VARCHAR,
  "num_list_users" BIGINT,
  "synonyms" VARCHAR,
  "en" VARCHAR,
  "ja" VARCHAR
);

Manga Ratinga

@kaggle.ddmasterdon_manga_2023_details_with_review.manga_ratinga

6.39 MB
1,204,816 rows
4 columns

CREATE TABLE manga_ratinga (
  "user" VARCHAR,
  "manga_id" BIGINT,
  "manga_title" VARCHAR,
  "score" BIGINT
);

Manga Raw

@kaggle.ddmasterdon_manga_2023_details_with_review.manga_raw

29.93 MB
71,357 rows
36 columns

CREATE TABLE manga_raw (
  "id" BIGINT,
  "title" VARCHAR,
  "main_picture_medium" VARCHAR,
  "main_picture_large" VARCHAR,
  "alternative_titles_synonyms" VARCHAR,
  "alternative_titles_en" VARCHAR,
  "alternative_titles_ja" VARCHAR,
  "start_date" TIMESTAMP,
  "end_date" TIMESTAMP,
  "synopsis" VARCHAR,
  "mean" DOUBLE,
  "rank" DOUBLE,
  "popularity" BIGINT,
  "num_list_users" BIGINT,
  "num_scoring_users" BIGINT,
  "nsfw" VARCHAR,
  "created_at" TIMESTAMP,
  "updated_at" TIMESTAMP,
  "media_type" VARCHAR,
  "status" VARCHAR,
  "genres" VARCHAR,
  "num_volumes" BIGINT,
  "num_chapters" BIGINT,
  "authors" VARCHAR,
  "pictures" VARCHAR,
  "background" VARCHAR,
  "related_anime" VARCHAR,
  "related_manga" VARCHAR,
  "recommendations" VARCHAR,
  "serialization" VARCHAR,
  "my_list_status_status" VARCHAR,
  "my_list_status_is_rereading" VARCHAR,
  "my_list_status_num_volumes_read" DOUBLE,
  "my_list_status_num_chapters_read" DOUBLE,
  "my_list_status_score" DOUBLE,
  "my_list_status_updated_at" TIMESTAMP
);