📅 2023-02-23 — Session: Developed and Optimized World Bank Data Analysis Workflow

🕒 20:50–22:15
🏷️ Labels: Data Analysis, Pandas, Geopandas, World Bank, Code Optimization
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal: The session aimed to develop a comprehensive data analysis workflow for World Bank investment datasets, focusing on data cleaning, merging, and visualization using Pandas and GeoPandas.

Key Activities:

  • Created a code workflow for processing World Bank investment datasets, incorporating data cleaning, merging, and visualization techniques.
  • Outlined a structured notebook for data analysis, detailing sections on setup, data preprocessing, analysis, conclusion, and references.
  • Explored World Bank resources for accessing country names and ISO codes, and provided instructions for downloading and using these resources in Python with Pandas.
  • Developed a Python function to integrate country names into a GeoDataFrame based on country codes, enhancing code modularity and readability.
  • Provided code improvement suggestions, including organizing imports, removing unused code, and cleaning up comments.
  • Offered code review suggestions for improved efficiency, such as function consolidation and enhanced documentation.
  • Updated Python code for GeoDataFrame intersection to address ShapelyDeprecationWarning errors and improve efficiency.

Achievements:

  • Successfully developed a modular and efficient data analysis workflow for World Bank datasets.
  • Enhanced code quality and efficiency through refactoring and optimization.

Pending Tasks:

  • Further test and validate the developed functions and workflows with additional datasets to ensure robustness and accuracy.