Refactor app.py to streamline data retrieval and processing for 'prop_frame', 'betsheet_frame', and 'pick_frame' by re-enabling MongoDB queries and enhancing data cleaning steps. Update user interface elements for improved clarity and functionality.

Comment out data retrieval and processing logic in app.py for prop, betsheet, and pick frames, while adding a warning message for users regarding the prop frame source being down. This simplifies the current data handling structure and prepares for future updates.

Ping

Enhance app.py by adding support for 'Walks (Hitters)' and 'Hits (Hitters)' prop categories, updating data processing logic accordingly. Modify median and flex file calculations to accommodate new categories, and update user interface messages for clarity.

Refactor app.py to replace Google Sheets API data retrieval with MongoDB for 'prop_frame', 'betsheet_frame', and 'pick_frame', while implementing dropna calls to clean data and enhance processing for betting models.

Update app.py to switch data retrieval from MongoDB to Google Sheets API for 'prop_frame', enhancing data processing by utilizing worksheet data instead of collection queries.

Add data frame copies for prop, betsheet, and pick data in app.py to enhance data processing structure for betting models.

Comment out additional data frame dropna calls in app.py to further simplify data processing for betting models, while keeping the structure intact for future use.

Comment out data frame dropna calls in app.py to simplify data processing for betting models, maintaining the structure for potential future use.

Refactor app.py to switch data retrieval from Google Sheets API to MongoDB for 'Prop_Trends' and 'Pick6_Trends', enhancing data processing efficiency while maintaining existing functionality.

Comment out additional percentage conversion lines in app.py to further simplify data processing for betting models, while preserving the structure for potential future use.

Comment out percentage conversion lines in app.py to simplify data processing for betting models, maintaining the existing structure for future adjustments.

Refactor app.py to reintegrate MongoDB data retrieval for Game_Betting_Model, restoring percentage conversions for ML_Value and Spread_Value while commenting out Google Sheets API calls for improved data processing.

Remove unnecessary percentage conversions for ML_Value and Spread_Value in app.py to streamline data processing for betting models.

Enhance data processing in app.py by converting percentage strings to float values for Win Percentage, Cover Spread Percentage, ML_Value, and Spread_Value. This ensures accurate calculations for betting models.

Refactor app.py to replace MongoDB data retrieval with Google Sheets API calls for the Game_Betting_Model. Commented out legacy MongoDB code and updated data processing to align with the new data source.

Update MongoDB database name in app.py from NHL_Database to MLB_Database to reflect the new data focus.

Refactor data processing in app.py to streamline the initialization of pitcher and hitter statistics. Updated variable names and removed unnecessary return values for improved clarity and efficiency.

Refactor app.py to integrate MongoDB for data storage and retrieval, replacing Google Sheets API calls. Added caching for connection initialization and improved tab styling in Streamlit.

Initial commit

initial commit