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Global Data Analytics Publication Metrics
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About
A curated collection of over 200 records detailing publications in the domain of Data Science and related topics. The data was compiled from one of the world's most popular retail websites, Amazon, capturing essential information such as customer ratings, purchase volumes, and pricing. This resource is valuable for exploring questions related to identifying best-selling titles, discovering underlying market patterns, and conducting in-depth exploratory data analysis of the data science publication landscape.
Columns
- Book_name / book title: The specific title of the publication. The list contains 182 unique titles, with 'Data Smart: Using Data Science to Transform Information into Insight' being the most frequently occurring record.
- Publisher / author: The individual or entity responsible for writing or publishing the book. This field includes approximately 200 unique values.
- Buyers: This metric represents the count of customers who have purchased the identical book. The average number of buyers is 324.
- Cover_type: Defines the physical format used to protect the publication, such as Paperback or Hardcover.
- stars: The user rating given to the book, measured on a scale of 0 to 5. The mean rating across the dataset is 4.25.
- Price: The cost of the book listed in US dollars. The maximum observed price is $175, with an average price of $38.60.
Distribution
The data is structured across 6 columns and contains 213 valid records. The file size is approximately 27.3 kB. Key observations include that 84% of the books listed are in the paperback cover format. In terms of popularity, the highest density of ratings falls between 4.50 and 5.00 stars, accounting for 133 records.
Usage
This data product is ideally suited for several analytical applications:
- Market research focused on the retail and shopping sector for technical books.
- Determining the characteristics of a best-selling data science publication.
- Analysing how pricing structure relates to buyer volume and consumer ratings.
- Performing detailed Exploratory Data Analysis (EDA) on book metadata.
Coverage
The data encompasses a range of subjects including Computer Science, Programming, Education, and Data Analytics, reflecting retail listings from Amazon. The source provides metrics for over 200 titles. It is expected that this catalogue will be updated on an annual basis.
License
CC0: Public Domain
Who Can Use It
- Academics and Students: To identify highly-rated and popular educational materials for studies in data science and machine learning.
- Data Analysts: To test statistical models and predictive analysis focused on retail consumption and user feedback.
- Publishing Houses: To gain market insight into successful formatting (cover type) and pricing strategies for technical literature.
- Developers: Those interested in utilising machine learning techniques to find hidden correlation patterns between ratings and sales metrics.
Dataset Name Suggestions
- Amazon Data Science Book Ratings and Sales
- Global Data Analytics Publication Metrics
- Data Science Book Catalogue for Retail Analysis
Attributes
Original Data Source: Global Data Analytics Publication Metrics
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