Refactored and Enhanced Python Code for Economic Data Analysis

📅 2023-12-23 — Session: Refactored and Enhanced Python Code for Economic Data Analysis

🕒 21:00–22:25
🏷️ Labels: Python, Data Analysis, Refactoring, Economic Analysis, Visualization
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to refactor and enhance Python code for economic data analysis, focusing on improving readability, efficiency, and alignment with economic principles.

Key Activities

• Refactored Python code for data analysis, enhancing readability and efficiency with better comments and variable naming.
• Resolved a ValueError during DataFrame merge by addressing column name conflicts.
• Enhanced code for analyzing covariance terms in economic data, improving clarity and significance.
• Improved visualization techniques for standardized covariance errors using Matplotlib.
• Modularized plotting logic and data processing functions to enhance maintainability and readability.
• Proposed a structured notebook outline for data analysis, covering sections from introduction to conclusion.
• Developed a framework for sales data analysis, including preprocessing and quantile analysis.
• Explored microshocks and macro variability in economic systems, focusing on risk management and market volatility.

Achievements

• Successfully refactored and modularized code, improving maintainability and efficiency.
• Enhanced understanding of covariance structures and economic variability through improved analysis and visualization.

Pending Tasks

• Further explore the implications of microshocks on macroeconomic variability through quantitative research.
• Implement additional visualization improvements for economic data analysis.