Enhanced Data Visualization and Processing in Python

📅 2023-10-14 — Session: Enhanced Data Visualization and Processing in Python

🕒 18:20–20:20
🏷️ Labels: Python, Data Visualization, Modularization, Documentation, Data Processing
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance data processing and visualization capabilities using Python, focusing on modularization, documentation, and effective plotting techniques.

Key Activities

• Documentation Essentials: Reviewed key documentation practices for resource-limited projects, emphasizing the importance of README files, inline comments, and architecture diagrams.
• Data Processing Adjustments: Implemented code adjustments to include base_str in unique combinations for data processing, ensuring accurate iteration over unique pairs.
• DataFrame Manipulation: Modified DataFrame operations to handle multiple groupers and applied filtering using compound boolean masks.
• Modularization: Refactored code to create a get_data_subset function, improving readability and maintainability.
• Time Series Plotting: Developed a plot_time_series() function for visualizing time series data, processing multiple files for unique pairs.
• [[Data Visualization]] Enhancements: Created subplots for CBA and CBT data, updated plotting code for economic indicators, and ensured consistent color mapping across plots.
• Advanced Plotting Techniques: Incorporated moving averages and median-based plots, with filled areas between percentiles for statistical analysis.

Achievements

• Successfully modularized data retrieval processes and enhanced code clarity.
• Improved visualization techniques with consistent color mapping and advanced plotting features.
• Updated documentation practices for better project management.

Pending Tasks

• Further testing of modularized functions in different data scenarios.
• Exploration of additional visualization techniques for complex datasets.