Refactored and Modularized Python Code for Economic Analysis

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

🕒 21:00–22:30
🏷️ Labels: Python, Data Analysis, Code Refactoring, Modularization, Economic Analysis
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance the readability, efficiency, and modularity of Python code used for economic data analysis, focusing on covariance and microshock dynamics.

Key Activities

  • Refactoring Python Code: Improved code readability and efficiency by refining comments, variable naming, and implementing optional visualization.
  • Resolving DataFrame Merge Issues: Addressed ValueError during DataFrame merge by resolving column name conflicts.
  • Enhancing Economic Analysis: Improved code for analyzing covariance terms in economic data, focusing on clarity and economic significance.
  • Plotting Enhancements: Enhanced visualization clarity for standardized covariance errors and modularized plotting logic for maintainability.
  • Data Processing Modularization: Developed modular functions for data processing, improving code organization and reusability.
  • Notebook Structure Proposal: Proposed a structured outline for organizing data analysis notebooks.
  • Sales Data Analysis Framework: Outlined a structured approach for sales data analysis, including preprocessing and quantile analysis.
  • Microshock Analysis: Reorganized code for analyzing microshocks, focusing on standard deviation and empirical shock data preparation.
  • Code Quality Improvements: Refactored code for improved readability and efficiency using best practices like vectorization with numpy.

Achievements

  • Successfully refactored and modularized Python code, enhancing maintainability and readability.
  • Resolved merge conflicts in DataFrame operations, ensuring data integrity.
  • Developed a comprehensive framework for economic and sales data analysis.

Pending Tasks

  • Further exploration of microshock dynamics and macro variability in economic systems is needed.
  • Implementation of the proposed notebook structure for future data analysis projects.

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