📅 2024-06-25 — Session: Economic Theory Rewriting and Data Processing Enhancements

🕒 13:20–15:40
🏷️ Labels: Teoría Económica, Optimalidad De Pareto, Python, Data Processing, Error Handling, Covariance
📂 Project: Business
⭐ Priority: MEDIUM

Session Goal

The session aimed to explore innovative approaches to economic theory, particularly focusing on the Pareto optimality, and to enhance data processing capabilities using Python.

Key Activities

  1. Rewriting Economic Theory: Explored innovative frameworks for rewriting economic theory with a focus on Pareto optimality, considering static and intertemporal contexts, and discussed implications of non-convex production functions.
  2. Structuring Economic Study: Developed a structured approach for an economic study aimed at academic recognition, covering problem identification, theoretical development, empirical analysis, political implications, and publication process.
  3. Critical Evaluation: Emphasized the importance of critically analyzing public figures and their economic theories, advocating for rigorous debate.
  4. Python Script Updates: Updated a Python script for CSV loading, addressing new naming conventions and data types.
  5. Error Handling in DataFrames: Solved a TypeError in DataFrame arithmetic operations by ensuring numeric columns are used and converting strings to numeric values.
  6. Groupby Error Handling: Addressed errors in groupby operations by ensuring only numeric data is processed, and revised functions for covariance computation.

Achievements

  • Developed innovative frameworks and structured approaches for economic theory and studies.
  • Enhanced Python scripts for data processing, improving error handling and data manipulation.

Pending Tasks

  • Further exploration of non-convex production functions in economic theory.
  • Continuous improvement of data processing scripts for robustness.

Labels

teoría económica, optimalidad de Pareto, Python, Data Processing, Error Handling, Covariance