Implement portfolio reset feature in app.py: add functionality to restore the original portfolio state and streamline the reset process for improved user experience in managing projections.

Refactor portfolio reset functionality in app.py: streamline the reset process by removing redundant filtering logic, ensuring a more efficient and clearer portfolio management experience.

Update 'Weighted Own' calculation in predict_dupes.py: adjust formula to account for the difference between maximum and minimum ownership values for improved accuracy in portfolio analysis.

Update selectbox labels in app.py: change "Select sort type" to "Select Sorting variable" and "Select trimming variable type" to "Select trimming variable" for improved clarity in user interface.

Enhance portfolio reset functionality in app.py: implement comprehensive filtering options for salary, finish percentile, and player selections, and update predict_dupes function to calculate 'Weighted Own' for improved accuracy in portfolio management.

Update reset button implementation in app.py: change button to use a unique key for state management, ensuring proper functionality in the trimming options section.

Add reset functionality for portfolio in app.py: store original portfolio state and implement reset button to restore it, enhancing user experience during trimming options.

Enhance portfolio trimming logic in app.py: add comprehensive filtering options based on salary, finish percentile, and player selections, and update predict_dupes function to adjust 'Product Own' calculation for improved accuracy.

Remove unused import of gmean from app.py and predict_dupes.py for cleaner code and improved performance.

Update trimming options in app.py: replace 'Geomean' with 'Product Own' for portfolio calculations, and ensure trimming logic is executed only upon form submission for improved user experience.

Refactor trimming options in app.py: encapsulate trimming selections within a form for better user interaction, and update the submission button for clarity in the trimming process.

Enhance portfolio filtering and trimming options in app.py: introduce expandable sections for filter and trimming options, update portfolio trimming logic to support geomean calculations, and improve export functionality with stack count adjustments.

Refactor portfolio filtering logic in app.py: streamline conditions for portfolio adjustments based on user selections, and ensure calculations are only performed when necessary. Add stack count adjustments for export options.

Update dataframe display logic in app.py: use current_page_data for improved clarity in pagination rendering.

Refactor pagination logic in app.py: move dataframe display to the correct position for improved user experience and clarity.

Fix index access and row dropping logic in trim_portfolio function in global_func/trim_portfolio.py for improved accuracy and performance.

Refactor trim_portfolio function in global_func/trim_portfolio.py: improve index handling and streamline row dropping logic for better performance.

Refactor trim_portfolio function in global_func/trim_portfolio.py: optimize iteration logic for filtering portfolios based on ownership type.

Add 'Trim Portfolio' button in app.py and implement trim_portfolio function in new global_func/trim_portfolio.py

Update site selection logic in app.py: move 'Select Site' dropdown above 'Clear data' button and adjust minimum lineup edge input precision.

Refactor portfolio loading logic in app.py: ensure portfolio is only loaded if not already in session state, and add minimum lineup edge input for filtering.

Refactor Streamlit UI in app.py: reorganize layout for clearer user interaction and restore 'Clear data' button functionality.

Add 'Product Own' calculation to portfolio in predict_dupes.py

Add initial Streamlit application with data loading, portfolio management, and optimization features

Initial Commit

initial commit