📅 2023-12-20 — Session: Structured GitHub Repository for Economic Analysis
🕒 04:00–05:30
🏷️ Labels: Github, Repository Structure, Data Analysis, Jupyter Notebooks, Python Scripting
📂 Project: Dev
⭐ Priority: MEDIUM
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.