📅 2023-07-26 — Session: Refactored and Modularized Python Code for Geospatial Data
🕒 04:00–07:50
🏷️ Labels: Python, Geospatial, Data Processing, Code Refactoring, Geopandas
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance the processing and analysis of geospatial data through improved Python code structure and functionality.
Key Activities
- Geospatial Data Processing: Loaded, processed, and saved geographical data in GeoJSON format, focusing on clarity through code comments.
- Data Manipulation with Pandas: Loaded CSV data into pandas DataFrame, converted it back to a dictionary, and utilized
select_dtypes()for data type selection. - Code Refactoring: Refactored Python code to improve organization, readability, and modularization, including the creation of reusable functions for data processing.
- Data Processing Enhancements: Revised scripts for merging geographic and aggregated data using Pandas and GeoPandas, ensuring consistency in variable naming and comments.
- Project Overviews and Naming: Reviewed the GeoCenso-Visualizer project and proposed SEO-focused repository names for better visibility.
Achievements
- Successfully refactored and modularized the Python code, improving its clarity and reusability.
- Enhanced data processing scripts for geospatial analysis, ensuring better integration and visualization of geographic census data.
Pending Tasks
- Further refinement of the GeoCenso-Visualizer project documentation and contribution guidelines.
- Finalization of SEO-optimized repository names for enhanced project discoverability.