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AI & Data Book Collection
Education & Learning Analytics
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Free
About
This dataset presents an extensive collection of books focused on various topics within data science. It was compiled with the aim of uncovering insights into the popularity of different data science subjects, common terminology used in titles and descriptions, and prominent authors or publishers in the field. The data was gathered via the Google Books API, concentrating on areas such as Python for data science, R programming, SQL, statistics, machine learning, natural language processing (NLP), deep learning, data visualisation, and data ethics, ensuring a diverse range of subjects. It includes books published within the last decade and is a valuable resource for anyone with an interest in data science, from those just starting out to seasoned practitioners.
Columns
- id: A unique identifier assigned to each book in the dataset.
- title: The main title of the book.
- subtitle: Additional metadata or a secondary title for the book.
- authors: The name or names of the author(s) responsible for writing the book.
- publisher: The name of the publishing house that released the book.
- published_date: The specific date on which the book was published.
- category: The primary category or genre to which the book belongs.
Distribution
The dataset is typically provided in a CSV file format, specifically
databook_details.csv, which has a size of approximately 624.69 kB. It is structured with 7 distinct columns and contains around 4090 records for most fields. The dataset is expected to be updated annually, ensuring its continued relevance.Usage
This dataset is ideal for several applications, including:
- Developing recommendation systems for books tailored to user interests.
- Identifying gaps and areas requiring further research within the existing data science literature.
- Facilitating general data analysis tasks to extract trends and patterns.
- Gaining insights into the prevalent data science topics and their popularity.
- Analysing common words and phrases used in book titles and descriptions.
- Identifying influential authors and publishing houses in the data science domain.
Coverage
The dataset's scope encompasses books related to data science topics such as Python, R, SQL, statistics, machine learning, NLP, deep learning, data visualisation, and data ethics. While the included publication dates range from 1962 to 2024, the collection process specifically focused on books released within the last 10 years to maintain currency. There is no specific geographic or demographic limitation, as it caters to a global audience interested in data science, from beginners to experienced professionals.
License
CC0: Public Domain
Who Can Use It
The dataset is intended for a broad audience, including:
- Beginners in data science: To explore foundational and advanced topics.
- Experienced practitioners: For research, literature review, and identifying niche areas.
- Developers: For building book recommendation engines or similar tools.
- Researchers: To analyse trends in data science publications, authors, and publishers.
- Educators: For curriculum development and understanding popular learning resources.
Dataset Name Suggestions
- Data Science Book Archive
- Modern Data Science Library
- AI & Data Book Collection
- Data Science Literature Digest
- Essential Data Science Books
Attributes
Original Data Source: AI & Data Book Collection
QUALITY