📅 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
- 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.
- 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.
- Critical Evaluation: Emphasized the importance of critically analyzing public figures and their economic theories, advocating for rigorous debate.
- Python Script Updates: Updated a Python script for CSV loading, addressing new naming conventions and data types.
- Error Handling in DataFrames: Solved a TypeError in DataFrame arithmetic operations by ensuring numeric columns are used and converting strings to numeric values.
- 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