📅 2023-03-31 — Session: Geospatial and Investment Data Processing and Analysis
🕒 19:30–20:10
🏷️ Labels: Python, Geospatial, Data Processing, Investment Analysis, Automation
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to organize and process geospatial and investment data using Python scripts, focusing on geospatial analysis, data merging, and investment calculations.
Key Activities
- Organized and executed Python scripts for processing geospatial data, including loading shapefiles, manipulating geolocation data, and saving results in GeoJSON format.
- Processed and merged geodataframes from multiple sources, creating unique project location IDs.
- Developed a script for intersecting GeoJSON files of administrative areas in Africa, analyzing intersections for violence and investment patterns.
- Calculated investment per capita in various administrative areas by aggregating data from multiple sources.
- Analyzed spatial overlap of Chinese and World Bank-funded projects using GeoDataFrames.
- Evaluated and suggested optimizations for script formatting and coding practices.
- Outlined a Python script for project data analysis using libraries like pandas and geopandas.
- Conducted exploratory analysis on World Bank project data, focusing on job-related investments.
- Automated data processing tasks, including URL gathering and PDF generation for World Bank projects.
Achievements
- Successfully organized and executed multiple Python scripts for geospatial data processing and analysis.
- Developed methods for investment analysis and data visualization.
- Automated several data processing tasks, improving efficiency.
Pending Tasks
- Further optimization of scripts for performance improvements.
- Additional analysis on the coexistence of Chinese and World Bank projects.
- Expansion of automated data processing to include more datasets.