📅 2023-02-23 — Session: Enhanced World Bank Data Processing Workflow
🕒 20:50–22:15
🏷️ Labels: Data Processing, World Bank, Geopandas, Python, Code Improvement
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to refine and enhance data processing workflows for World Bank investment datasets using Python libraries such as Pandas and GeoPandas.
Key Activities
- Developed a code workflow for processing and analyzing World Bank investment datasets, focusing on data cleaning, merging, and visualization.
- Outlined a structured notebook for data analysis, covering setup, preprocessing, analysis, and documentation sections.
- Explored World Bank resources for country names and ISO codes, integrating these into data workflows.
- Improved code quality through suggestions for organizing imports, removing unused code, and enhancing readability.
- Implemented a Python function to add country names to GeoDataFrames, improving data manipulation capabilities.
- Reviewed and optimized code for efficiency, focusing on function consolidation and parameterization.
- Developed a Python function for loading and processing data from CSV or Excel files, showcasing modular coding practices.
- Updated Python scripts to handle GeoDataFrame intersections more efficiently, addressing ShapelyDeprecationWarnings.
Achievements
- Successfully enhanced the data processing workflow for World Bank datasets, incorporating best practices in data manipulation and code quality.
- Improved the efficiency and readability of Python scripts used in geospatial data analysis.
Pending Tasks
- Further optimization of data processing functions for scalability and performance.
- Exploration of additional World Bank datasets for comprehensive analysis.