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The Books Dataset: Sales, Ratings, and Publication provides comprehensive information on various aspects of books, including their publishing year, author details, ratings given by readers, sales performance data, and genre classification. The dataset consists of several key columns that capture important attributes related to each book.
The Publishing Year column indicates the year in which each book was published. This information helps in understanding the chronological distribution of books in the dataset.
The Book Name column contains the titles of the books. Each book has a unique name that distinguishes it from others in the dataset.
The Author column specifies the name(s) of the author(s) responsible for creating each book. This information is crucial for understanding different authors' contributions and analyzing their impact on sales and ratings.
The language_code column represents a specific code assigned to indicate the language in which each book is written. This code serves as a reference point for language-based analysis within the dataset.
Each author's rating is captured in the Author_Rating column. This rating is based on their previous works and serves as an indicator of their reputation or acclaim among readers.
The average rating given by readers for each book is recorded in the Book_average_rating column. This value reflects how well-received a particular book is by its audience.
The number of ratings given to each book by readers can be found in the Book_ratings_count column. This metric helps gauge reader engagement and provides insights into popular or widely-discussed books within this dataset.
Books are classified into different genres or categories which are mentioned under the genre column. Genre classification allows for analyzing trends across specific literary genres or identifying patterns related to certain types of books.
Sales-related data includes both gross sales revenue (gross sales) generated by each book and publisher revenue (publisher revenue) earned from these sales transactions. These numeric values provide insights into financial performance aspects associated with the book market.
The sale price column denotes the specific price at which each book is sold. This information helps evaluate pricing strategies and their potential impact on sales figures.
Sales performance is further quantified through the sales rank column, which assigns a numerical rank to each book based on its sales performance. This ranking system aids in identifying high-performing books within the dataset.
Lastly, the units sold column captures the number of units of each book that have been sold. This data highlights popular books based on reader demand and serves as a crucial measure of commercial success within the dataset.
Overall, this expansive and comprehensive Books Dataset
Introduction:
Getting Familiar with the Columns: The dataset contains multiple columns that provide different kinds of information:
Book Name: The title of each book.
Author: The name of the author who wrote the book.
language_code: The code representing the language in which the book is written.
Author_Rating: The rating assigned to the author based on their previous works.
Book_average_rating: The average rating given to the book by readers.
Book_ratings_count: The number of ratings given to the book by readers.
genre: The genre or category to which the book belongs.
gross sales: The total sales revenue generated by each book.
publisher revenue: The revenue earned by publishers from selling each book.
sale price: The price at which each copy of a book is sold.
sales rank: A numeric value indicating a book's rank based on its sales performance in comparison to other books within its category (genre).
units sold : Total number of copies sold for each specific title.
Understanding Numeric and Textual Data: Numeric columns in this dataset include Publishing Year, Author_Rating, Book_average_rating, Book_ratings_count,gross sales,publisher revenue,sale price,sales rank and units sold; these provide quantitative insights that can be used for statistical analysis and comparisons.
Additionally,the columns 'Author','Book Name',and 'genre' contain textual data that provides descriptive elements such as authors' names and categorization genres.
- Exploring Relationships Between Data Points: By combining different co...
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TwitterIn 2024, the German book market generated a revenue of almost *** billion euros from print book sales and around *** million euros from e-books. Revenue for both segments has remained stable during the period of consideration, with e-book revenue even rising in recent years. The German book market lives on. Book retail Despite repeated dire warnings about reading dying out and bookshops suffering as a result, Germans have not stopped reading or buying books, whether physically or online. Of course, the traditional book trade does face challenges, especially with the rise of e-books. Revenue development in the German book trade has fluctuated during the last two years, which was undoubtedly still influenced by the COVID-19 lockdowns of 2020 and 2021, when physical book retail locations were closed for months on end and book sales through those channels took a big hit. Brick and mortar shops stocking books were still the leading source of revenue among book buying locations, followed by mail order (whether from a shop or buying online in general). Curled up with a book German readers reach for a variety of genres when making their book choices. Preferences and trends, or, more specifically, sales figures, change periodically. Most recently, leading subjects included non-fiction, fiction and advice/self-help.
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E-Book Market Size 2025-2029
The e-book market size is forecast to increase by USD 14.52 billion, at a CAGR of 10.7% between 2024 and 2029.
Major Market Trends & Insights
North America dominated the market and accounted for a 45% growth during the forecast period.
By the Product - Consumer e-book segment was valued at USD 7.86 billion in 2023
By the Platform - Smartphones segment accounted for the largest market revenue share in 2023
Market Size & Forecast
Market Opportunities: USD 163.63 billion
Market Future Opportunities: USD USD 14.52 billion
CAGR : 10.7%
North America: Largest market in 2023
Market Summary
The market continues to evolve, with various formats gaining traction among publishers and readers. According to recent studies, the number of e-books sold has surpassed print books, representing a significant shift in consumer preferences. In 2020, e-books accounted for approximately 25% of all book sales, marking a noticeable increase from the previous year. Moreover, the market's dynamism extends to the diverse range of applications across industries. Education, business, and entertainment sectors have embraced e-books due to their convenience, accessibility, and cost-effectiveness.
However, this growth trajectory comes with challenges, such as privacy concerns. Reports indicate that over 50% of e-book users have experienced privacy breaches, with unsecured downloads and unencrypted files being common vulnerabilities. Despite these challenges, the market's continuous evolution underscores its potential for further growth and innovation.
What will be the Size of the E-Book Market during the forecast period?
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The market exhibits a steady expansion, with current sales accounting for approximately 20% of the global publishing industry's revenue. This figure underscores the increasing preference for digital content among businesses and consumers alike. Looking ahead, industry experts project a 15% annual growth rate, indicating a significant expansion in the coming years. A comparison of sales trends reveals a noticeable shift towards e-books. In 2015, e-books represented 17% of total book sales, while in 2020, they accounted for 23% of the market.
This growth trajectory underscores the market's continuous evolution and the increasing importance of digital content in the publishing sector. Despite this growth, print books still maintain a substantial market share, accounting for around 77% of total book sales in 2020. However, the gap between e-books and print books is closing, highlighting the potential for further market disruption and growth in the digital publishing space.
How is this E-Book Industry segmented?
The e-book industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Product
Consumer e-book
Professional e-book
Educational e-book
Platform
Smartphones
Tablet and laptops
Desktops
Smart TVs
Business Model
Pay-per-download
Subscription-based
Freemium
Lending/Borrowing
Genre
Fiction
Non-fiction
Young Adult
Comics/Graphic Novels
Geography
North America
US
Canada
Europe
France
Germany
Spain
UK
Middle East and Africa
UAE
APAC
China
India
Japan
South Korea
South America
Brazil
Rest of World (ROW)
By Product Insights
The consumer e-book segment is estimated to witness significant growth during the forecast period.
The market, a significant segment of digital content consumption, is experiencing notable growth driven by the increasing popularity of fiction books among readers. Approximately 60% of e-Book sales stem from fiction titles, with young adult literature accounting for a substantial portion of this demand. European countries, including Germany, Italy, the Netherlands, and Belgium, generate a substantial portion of their e-Book revenues from fiction sales. Fiction books, categorized into literary and commercial genres, have seen a surge in demand due to evolving reading habits. The allure of compelling stories has made fiction a preferred choice for many individuals.
For instance, literary fiction offers insightful narratives and character development, while commercial fiction caters to popular trends and genres. Moreover, the adoption of technology and the convenience it offers have contributed to the growth of the market. For example, e-Books can be accessed instantly, and their portability makes them an ideal choice for avid readers. Additionally, e-Books offer features like adjustable font sizes, text-to-speech, and note-taking capabilities, enhancing the
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This dataset provides an in-depth analysis of the best-selling books in Spain. It offers comprehensive information on the top 100 titles, including their ranking, author, title, language of publication, genre, ISBN and EAN numbers and respective publisher details such as translator and illustrator. Furthermore, it also includes data about other important metrics such as the published date (where known), dimensions and weight plus number of pages making it ideal for those interested in obtaining a comprehensive insight into Spain's book market.
Those wanting to gauge success within the Spanish book industry can benefit from valuable insights gathered from this dataset. Publishers looking for new opportunities within this market can gain a better understanding about popular authors/genres by analysing the rank positions that titles have achieved as well as useful information regarding hardcover versus paperback releases or books with availability in various languages. Similarly researchers keen to assess trends regarding cultural phenomena found within Spanish society may find insight into potential correlations between reading material preferences and societal topics that define current interests when referring to literature sales.
As such this dataset with its relevant attributes could offer users many opportunities which could further enable exploration into other areas beyond just traditional publishing insights including among others: education links with publishing markets; foreign exchange students' interests when studying abroad compared to autochthonous readerships; festivals that promote culture through literature etc. All these could open up exciting new avenues for publishers as well potential clients who advertise alongside these products.
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This dataset provides comprehensive information about the top 100 best-selling books in Spain in 2020, including ranking, author, title, language of publication, genre, ISBN and EAN, publisher, translator and illustrator. This data can be used to gain an understanding of the trendiest books in Spain at the time of dataset compilation as well as learn more about successful authors or publishers. It is especially useful for bookstores looking to increase their market share in Spain by stocking popular titles from popular authors or publishers.
The following are practical steps on how to use this dataset: - Identify the columns that contain relevant data for your analysis - these could include Ranking (Puesto), Author (Autor), Title (TÃtulo), Genre (Materias), Publisher (Editorial) and Translator/Illustrator names if they are applicable to your project goals; - Explore each column individually and make note of any trends you find across all 100 titles; - Cross reference your findings with other sources such as IMDb if specific names come up;
- Use filtering techniques like sorting by Ranking (lowest to highest) or Genre to narrow down the list focused around any given criteria;
- Finally analyse various metrics such as number of titles per author/publisher/genre etc., most popular topics among top ranking books etc., for insightful conclusions about best-selling books in Spain at this particular time
- Analyzing and predicting the sales of new titles by comparing their genre, author, number of pages and other relevant features to the success of the books present in the dataset.
- Predicting trends in Spain's book market by analyzing how ratings are distributed between different genres, authors and writers at different points in time since books were published or reproduced.
- Measuring engagement with specific topics, authors or genres within Spain’s book market by tracking how often specific titles are included in best-selling lists over time
If you use this dataset in your research, please credit the original authors. Data Source
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
File: libros_mas_vendidos.csv | Column name | Desc...
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The E-Book Market Report is Segmented by Revenue Model (Subscription, Pay-Per-Download, Freemium/Ad-supported, and Institutional Licensing), Genre (Fiction, Non-Fiction, Education and Academic, Comics and Graphic Novels, and Professional and Technical), End-User (Individual Consumers, and Institutional), and Geography. The Market Forecasts are Provided in Terms of Value (USD).
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TwitterAccording to the results of a survey held in late 2022, books falling into the history genre were most read by American book readers in that year, with ** percent of book lovers and readers saying they had read a history book in 2022. Biographies and mystery books were also popular, whereas romance and self-help books were less read.
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TwitterThe average selling price of books in the children and young adult genre of the Indian book market was *** Indian rupees in 2021. This was a decrease from the previous year as the average selling price across the overall market dropped by *** percent that year. Thus, the sales performance of the children's segment set new records with the volume of books sold in 2021 grossing over ***********, valued at *** billion Indian rupees.
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TwitterRegardless of the provider they use, U.S. consumers stream all types of genres. How has the popularity of science fiction / fantasy as online content genre in the U.S. changed over the past years? There is only a slight decrease from 2022 Q4 to the current value. This doesn't represent the overall trend, which is characterized by fluctuating values. While sience fiction and fantasy content watchers were showing this development in the recent past, many other genres had peaks and valleys in popularity, possibly due to a constant stream of new hit shows being hyped among viewers. Amidst streaming wars and password sharing breakdowns, many suppliers are expanding their catalogues to garner even bigger audiences. To see what type of content Netflix and their rivals should invest into next, we gathered the overview of the preferred digital video content by genre in the U.S. benchmarking sience fiction and fantasy content watchers among other genres. The survey was conducted online among 3675 to 8858 respondents per quarter in the United States, between 2019 and 2023. Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than 2,000,000 interviews.
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Learn how you can add new datasets to our index.
Facebook
TwitterBy Josh Murrey [source]
The Books Dataset: Sales, Ratings, and Publication provides comprehensive information on various aspects of books, including their publishing year, author details, ratings given by readers, sales performance data, and genre classification. The dataset consists of several key columns that capture important attributes related to each book.
The Publishing Year column indicates the year in which each book was published. This information helps in understanding the chronological distribution of books in the dataset.
The Book Name column contains the titles of the books. Each book has a unique name that distinguishes it from others in the dataset.
The Author column specifies the name(s) of the author(s) responsible for creating each book. This information is crucial for understanding different authors' contributions and analyzing their impact on sales and ratings.
The language_code column represents a specific code assigned to indicate the language in which each book is written. This code serves as a reference point for language-based analysis within the dataset.
Each author's rating is captured in the Author_Rating column. This rating is based on their previous works and serves as an indicator of their reputation or acclaim among readers.
The average rating given by readers for each book is recorded in the Book_average_rating column. This value reflects how well-received a particular book is by its audience.
The number of ratings given to each book by readers can be found in the Book_ratings_count column. This metric helps gauge reader engagement and provides insights into popular or widely-discussed books within this dataset.
Books are classified into different genres or categories which are mentioned under the genre column. Genre classification allows for analyzing trends across specific literary genres or identifying patterns related to certain types of books.
Sales-related data includes both gross sales revenue (gross sales) generated by each book and publisher revenue (publisher revenue) earned from these sales transactions. These numeric values provide insights into financial performance aspects associated with the book market.
The sale price column denotes the specific price at which each book is sold. This information helps evaluate pricing strategies and their potential impact on sales figures.
Sales performance is further quantified through the sales rank column, which assigns a numerical rank to each book based on its sales performance. This ranking system aids in identifying high-performing books within the dataset.
Lastly, the units sold column captures the number of units of each book that have been sold. This data highlights popular books based on reader demand and serves as a crucial measure of commercial success within the dataset.
Overall, this expansive and comprehensive Books Dataset
Introduction:
Getting Familiar with the Columns: The dataset contains multiple columns that provide different kinds of information:
Book Name: The title of each book.
Author: The name of the author who wrote the book.
language_code: The code representing the language in which the book is written.
Author_Rating: The rating assigned to the author based on their previous works.
Book_average_rating: The average rating given to the book by readers.
Book_ratings_count: The number of ratings given to the book by readers.
genre: The genre or category to which the book belongs.
gross sales: The total sales revenue generated by each book.
publisher revenue: The revenue earned by publishers from selling each book.
sale price: The price at which each copy of a book is sold.
sales rank: A numeric value indicating a book's rank based on its sales performance in comparison to other books within its category (genre).
units sold : Total number of copies sold for each specific title.
Understanding Numeric and Textual Data: Numeric columns in this dataset include Publishing Year, Author_Rating, Book_average_rating, Book_ratings_count,gross sales,publisher revenue,sale price,sales rank and units sold; these provide quantitative insights that can be used for statistical analysis and comparisons.
Additionally,the columns 'Author','Book Name',and 'genre' contain textual data that provides descriptive elements such as authors' names and categorization genres.
- Exploring Relationships Between Data Points: By combining different co...