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GeeksforGeeks Article Metadata Collection
Data Science and Analytics
Tags and Keywords
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Free
About
This collection captures metadata for approximately 34,000 articles published on GeeksforGeeks. It provides essential details such as the article title, the contributing author, the date of the last update, and the link to the original content. The purpose is to inspire learning and facilitate data analysis, enabling learners to delve into publishing patterns and popular topics within the technical domain.
Columns
The dataset is structured across five key columns, detailing information about each article:
- title: The primary title given to the article.
- author_id: Identifies the author responsible for the article.
- last_updated: Indicates when the specific article was most recently updated.
- link: Provides the direct URL to the article on the GeeksforGeeks website.
- category: The classification or difficulty level assigned to the article (e.g., medium, easy).
Distribution
The data file, named
articles.csv, has a file size of 5.47 MB. It contains a total of 5 columns and includes valid record counts reaching 34.6 thousand entries. All records appear unique based on the article link, and the majority of columns have no missing data, ensuring a high level of usability. The content focuses specifically on article metadata.Usage
This dataset is ideally suited for Data Analytics and Exploratory Data Analysis (EDA) projects. Ideal applications include:
- Determining the most prolific authors based on their total number of publications.
- Conducting frequency analysis of article publications, broken down by day, month, or year.
- Filtering articles by specific authors or categories.
- Analysing category distribution to identify popular topic areas.
- Developing tools for tag-based searching (e.g., filtering for articles related to 'python').
Coverage
The dataset focuses on articles and technical topics available on GeeksforGeeks. While specific geographic or demographic coverage is not applicable, the time coverage is indicated by the
last\_updated field. The dataset is expected to be updated annually, providing ongoing relevance for tracking trends in technical publishing.License
CC BY-NC-SA 4.0
Who Can Use It
The dataset is intended for technical learners, data science students, and analysts. Users interested in learning practical data analytics skills will find the structure and context valuable. It is also suitable for researchers looking to study content trends in online education and technology sectors.
Dataset Name Suggestions
- GeeksforGeeks Article Metadata Collection
- Technical Content Publishing Trends
- GfG Educational Article Analysis Data
- Article Author and Frequency Dataset
Attributes
Original Data Source: GeeksforGeeks Article Metadata Collection
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