Refactored and Enhanced Data Processing Pipeline

📅 2023-08-20 — Session: Refactored and Enhanced Data Processing Pipeline

🕒 04:00–05:20
🏷️ Labels: Python, Data Processing, Code Refactoring, Geopandas, Data Visualization
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal: The session aimed to refactor and enhance the Python code for data processing tasks, focusing on code clarity, efficiency, and resolving specific errors.

Key Activities:

• Refactored Python scripts to improve code clarity and efficiency, focusing on data loading, preprocessing, and merging operations.
• Addressed a MergeError in DataFrames with multi-level columns by flattening columns and correctly performing merge operations.
• Implemented methods for dropping MultiIndex levels in Pandas DataFrames and merging them with specific keys.
• Resolved errors related to the absence of an active geometry column in GeoDataFrames for plotting with GeoPandas.
• Troubleshot NaN values in geometry columns affecting plotting, ensuring data cleaning processes were in place.
• Developed techniques for displaying tables and plots for districts and sections using IPython and Matplotlib.
• Guided the overlay of data on maps using Matplotlib, including transparency adjustments.
• Created a function to compute zoom levels based on bounding box widths for map image processing.

Achievements:

• Enhanced code readability and maintainability through refactoring.
• Successfully resolved data merging and plotting errors, improving the data visualization process.
• Developed reusable functions for zoom level calculation and data overlay on maps.

Pending Tasks:

• Further testing and validation of the refactored code in different data processing scenarios.
• Exploration of additional optimization techniques for large datasets.