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Data Science User Rank and Medal Data
Data Science and Analytics
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About
This collection offers detailed user ranking information from the Kaggle platform, encompassing performance across four key areas: Notebooks, Datasets, Competitions, and Discussions. It allows for detailed analysis of user achievement levels, scores, and medal counts, providing significant insights into the platform's hierarchy and user engagement metrics.
Columns
rank: The numerical ranking position of the user.points: The score accrued by the user.Status: The achievement level of the user (e.g., Expert, Master).profile url: The hyperlink directing to the user's public profile.name: The user's unique username.joined: The date the user joined the platform.Gold medals: The total count of gold medals earned.silver medals-item 2: The total count of silver medals earned.bronze medals: The total count of bronze medals earned.
Distribution
The data is structured in a tabular format, typically supplied as a CSV file (one sample file is 813.35 kB). There are 9 columns of data available. The collection contains approximately 5,000 records of ranked users specific to the Competition category. The information is expected to be updated on a monthly basis, ensuring currency of the rankings.
Usage
- Analysing user progression and achievement paths within the data science community.
- Benchmarking success metrics across various user levels.
- Studying the distribution of medals (Gold, Silver, Bronze) among highly ranked members.
- Tracking fluctuations in user scores and rankings over time.
Coverage
The scope of this data is platform-wide, focusing on user statistics gathered from the Kaggle environment across four distinct categories: Notebook, Dataset, Competitions, and Discussions. Temporal coverage is indicated by 'joined' dates, showing activity for users who joined as far back as four or five years ago.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For examining community dynamics and quantifying expertise distribution.
- Academics/Researchers: To model user engagement and the development of skill hierarchy.
- Recruiters and Hiring Managers: To identify highly ranked or highly decorated individuals for potential opportunities.
Dataset Name Suggestions
- Kaggle Achievement Hierarchy Metrics
- Data Science User Rank and Medal Data
- Kaggle Competitions User Performance
Attributes
Original Data Source: Data Science User Rank and Medal Data
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