📅 2023-12-20 — Session: Refactored and Optimized Data Processing Scripts
🕒 13:20–14:55
🏷️ Labels: Python, Data Processing, Code Refactoring, Jupyter Notebooks, Optimization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance the efficiency and maintainability of data processing scripts and Jupyter notebooks used in economic network analysis.
Key Activities
- Revised a prompt for Jupyter Notebook analysis focusing on code functionality and integration.
- Proposed a restructuring plan for economic network analysis notebooks to improve modularity and coherence.
- Refactored Python code for data processing using Dask and Pandas, improving readability and maintainability.
- Streamlined degree distribution plots notebook using Pandas and Matplotlib for clarity and efficiency.
- Debugged and corrected Python code for plotting degree distributions, addressing runtime warnings and errors.
- Improved the structure of a data preparation script for better modularization and organization.
- Explored efficient line counting techniques in Python and Bash for large file processing.
Achievements
- Successfully refactored and optimized multiple data processing scripts and notebooks.
- Enhanced code readability, maintainability, and efficiency across several projects.
- Resolved issues in data visualization scripts, ensuring proper functionality.
Pending Tasks
- Further testing and validation of the refactored scripts and notebooks are required to ensure robustness in different scenarios.
- Additional documentation and comments may be needed for some of the newly structured scripts.