We have set of Python scripts for various tasks related to stock data and analysis. Here's a brief summary of each script:

1. get_stock_names.py:

   • Purpose: Retrieves stock names and their corresponding Moneycontrol site links.
   • Output: Stores the information in a file named stock.csv.

2. get_swot_details.py:

   • Purpose: Reads stock.csv and calculates SWOT scores along with MC Essential scores for each stock.
   • Output: Creates a file named swot_details.csv containing the calculated scores.

3. streamlit-swot.py:

   • Purpose: Utilizes Python Streamlit to render a webpage for easy viewing of collected SWOT details.
   • Output: Provides a user-friendly interface to access the SWOT analysis data.
   • Execute: Run this program as streamlit run streamlit-swot.py after installing the necessary packages.

4. MoneyControl.ipynb:

   • Purpose: Designed to be used in Jupyter notebook, allowing real-time data science operations related to Moneycontrol SWOT data.

These scripts seem to form a cohesive workflow where you gather stock data, perform SWOT analysis, visualize the results using Streamlit, and have the flexibility for on-the-fly data science operations in Jupyter notebook using MoneyControl.ipynb.