A comprehensive data analysis project that examines user behavior and patterns on Codeforces, focusing on identifying trends, anomalies, and insights in competitive programming.
This project performs in-depth analysis of Codeforces data, including:
- User rating distribution and progression patterns
- Activity patterns based on geography and organizations
- Performance metrics across different programming competitions
- Participation trends over time
- Rating distribution across different regions and organizations
- Performance comparison between different user groups
- Success metrics for various programming languages and problem categories
- Identification of key performance indicators (KPIs) for competitive programmers
- Analysis of contest participation and its correlation with performance
- Time-series analysis of user activity and performance metrics
- Asynchronous data collection from Codeforces API
- Efficient batching of API requests to handle rate limits
- Robust error handling and retry mechanisms
- Data cleaning and transformation pipelines
- Feature engineering for analytical metrics
- Efficient storage and retrieval of processed data
- Python-based data analysis stack (pandas, numpy)
- Statistical analysis and visualization
- Jupyter notebooks for exploratory data analysis
- User rating distributions and histograms
- Performance trends over time
- Geographic heatmaps of user activity
- Correlation matrices of different performance metrics
- Time-series analysis of contest participation
- Python 3.8+
- pip (Python package manager)
- Jupyter Notebook (for exploratory analysis)
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Clone the repository:
git clone [your-repository-url] cd CodeSuses -
Install dependencies:
pip install -r requirements.txt
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Run the analysis:
python extraction/fulldata.py jupyter notebook analysis/
Explore the analysis/ directory for Jupyter notebooks containing:
- Data exploration and visualization
- Statistical analysis of user behavior
- Pattern recognition in contest participation
- Performance prediction models
We welcome contributions to enhance our analysis! Please feel free to submit a Pull Request with your analytical insights or improvements.
This project is licensed under the MIT License - see the LICENSE file for details.
- Codeforces for providing the API and data
- The competitive programming community for their valuable insights