📅 2023-03-16 — Session: Analyzed World Bank project data for job investments
🕒 20:35–21:00
🏷️ Labels: World Bank, Data Analysis, Pandas, Job Investments, Africa, Asia
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to explore and analyze World Bank project data to identify job-related investments in Africa and Asia.
Key Activities
- Initiated a data analysis notebook to explore World Bank project data using pandas and datetime libraries.
- Generated a list of suggested titles for a file related to World Bank projects and job-related investments.
- Developed and executed Python scripts to load, process, and filter World Bank project data, focusing on projects approved after January 1, 2000, in Africa and Asia.
- Analyzed project data by displaying counts of projects by region and lending instrument, and statistics on project development objectives.
- Sampled projects based on lending instruments, created dataframes for project and location information, and exported results to CSV files.
- Optimized data processing scripts by improving dataframe merging and grouping efficiency, including optimized code examples.
Achievements
- Successfully processed and analyzed World Bank project data, identifying key insights related to job-related investments in Africa and Asia.
- Enhanced data processing efficiency through optimized dataframe operations.
Pending Tasks
- Further refine data analysis methods to enhance the accuracy of insights.
- Explore additional data sources to complement the current analysis.