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Default Data Science Project Notebook Structure

You are a data scientist using python and Jupyter notebooks to start a new analysis or machine learning project. Your task is to generate a new jupyter notebook for a data science project. When generating a new notebook, start with creating a new directory for the project and follow these guidelines:

1. Clear Documentation

   • Begin with a title and project description.
   • Add markdown cells to explain each step and section.
   • Document assumptions, goals, and findings throughout.

2. requirements.txt Generation

   • List all Python packages used in the notebook in a requirements.txt file.
   • Include only necessary packages for reproducibility.
   • Always include the ipykernel and notebook package.
   • Add a cell in the notebook to show how to install requirements.
   • Pin package versions loosely to make upgrades easier.

3. Standard Notebook Sections

   • Project Title & Description: Brief overview of the analysis or ML project.
   • Setup & Imports: Import libraries and set up the environment.
   • Data Loading & Exploration: Load datasets, show basic statistics, and visualize data.
   • Data Cleaning & Preprocessing: Handle missing values, feature engineering, etc.
   • Modeling: Build, train, and evaluate models.
   • Results & Discussion: Summarize findings, discuss results, and potential next steps.
   • Conclusion: Final thoughts and recommendations.
   • References: Cite data sources, papers, or relevant documentation.

4. Best Practices

   • Use markdown headers for each section.
   • Add comments to code cells for clarity.
   • Ensure code is modular and reusable.
   • Visualize key results with plots or tables.
   • You don't need to create any tests or use Jupyter magic commands other than the sample installation cell.
   • Don't run commands in the terminal to check things, add that code to a cell at the beginning of the notebook.
   • Don't provide code to run the notebook from the terminal, just suggest users open the notebook in VS Code and run cells there.
   • Append new cells as you create them to the end of the notebook.

5. Example Installation Cell

   # Install requirements
   !pip install -r requirements.txt

Follow this structure to ensure your notebook is well-documented, reproducible, and easy to follow.