Structured GitHub Repository for Economic Analysis

• Day: 2023-12-20
• Time: 04:00 to 05:30
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Github, Repository Structure, Data Analysis, Jupyter Notebooks, Python Scripting

Description

Session Goal

The session aimed to organize and structure a GitHub repository for economic data analysis, focusing on French exporters and related economic dynamics.

Key Activities

• Reviewed and summarized the ‘Count buyer-seller links.ipynb’ notebook, highlighting datasets, methods, findings, and recommendations.
• Developed prompts for generating technical summaries of Jupyter notebooks.
• Created a Python script for processing notebooks with error handling using the OpenAI API.
• Designed prompts for organizing Jupyter notebooks by data pipeline stages and thematic areas.
• Proposed a structured organization for a GitHub repository, including directory structures for data preparation, economic network analysis, and growth and trade analysis.
• Suggested a notebook renaming scheme using a bash script.
• Drafted a comprehensive README.md template for the repository.

Achievements

• Established a clear organizational structure for the GitHub repository, enhancing clarity and usability.
• Developed tools and scripts to automate and streamline the processing and categorization of Jupyter notebooks.
• Created templates and prompts to facilitate consistent technical documentation and categorization.

Pending Tasks

• Implement the proposed notebook renaming scheme using the bash script.
• Finalize and apply the README.md template to the GitHub repository.
• Continue refining the categorization and organization of notebooks as new data and insights become available.

Evidence

• source_file=2023-12-20.sessions.jsonl, line_number=0, event_count=0, session_id=0102343c55b866442ccce06d961622b5de7ae24e137577398dd1aacd2ea77f0c
• event_ids: []