Update column layout for export options in app.py: adjust button column widths to improve UI spacing and enhance user experience when downloading portfolios.

Refactor custom export options in app.py: reorganize layout to separate buttons for adding all and selected rows to the custom export, improving user interface clarity and functionality.

Add custom export functionality in app.py: introduce options to add all or selected rows from the merge DataFrame to the custom export, enhancing user control over data selection and improving export flexibility.

Update stack inclusion logic in app.py: modify condition to check for sport types (NFL, MLB, NHL) instead of 'Stack' column, enhancing stack selection functionality for specific sports.

Update size selection logic in app.py: conditionally include size options based on sport type, ensuring appropriate functionality for NFL, MLB, and NHL while defaulting to an empty selection for others.

Update excluded columns in app.py: replace 'Dupes' with 'Size' in the list of excluded columns to reflect recent changes in player size selection functionality.

Add size selection functionality in app.py: introduce options to include player sizes in lineups, enhancing user control over player configurations and improving data representation.

Update team selection options in app.py: switch from using 'working_frame' to 'projections_df' for team inclusion and removal, ensuring accurate data representation in player configurations.

Add team selection functionality in app.py: introduce options to include and remove teams from lineups for enhanced user control over player configurations.

Enhance stack selection functionality in app.py: update stack inclusion and removal options for improved user control over lineup configurations.

Refactor exposure calculation in app.py: remove percentage formatting from 'Exposure' field to ensure consistent raw value representation across player statistics.

Refactor exposure calculation in app.py: update 'Exposure' field to store raw percentage values instead of formatted strings for improved data handling and consistency in player statistics.

Refactor player statistics display in app.py: update 'Lineup Count' to show raw counts and add 'Exposure' percentage for enhanced clarity in player usage analysis.

Update player and stack statistics display in app.py: modify 'Lineup Count' to include percentage of total lineups for improved clarity and insight into player usage.

Fix condition for stack statistics display in app.py: update header check to use 'columns' instead of 'headers' for accurate data retrieval.

Enhance stack summary in app.py: modify sorting to include dropping duplicates for improved data accuracy and clarity in displayed statistics.

Enhance tab layout for player and stack statistics in app.py: replace column layout with tabs for improved organization and user navigation, and adjust stack statistics condition for better data handling.

Refactor player and stack statistics display in app.py: streamline player summary calculations and add stack summary section for enhanced data visualization and user experience.

Adjust column layout in portfolio section of app.py: change from 3 to 2 columns for improved UI in the projections display.

Refactor contest size and strength input in app.py: replace individual input fields with a form layout for better organization and user experience, and ensure portfolio reset functionality is maintained upon submission.

Merge branch 'main' of https://huggingface.co/spaces/Multichem-PD/DFS_Portfolio_Manager

Update sport selection options in app.py: add 'WNBA' to the list of available sports in the dropdown menu, enhancing user choice and application functionality.

Update app.py

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Update app.py

Improve error handling for CSV file names in app.py: add a try-except block to ensure robust retrieval of names from session state, enhancing application stability and user experience.

Enhance user interface in app.py: add a fourth column for game type selection, reorganize input fields for site, sport, contest size, and field strength, and improve layout for better user interaction and clarity.

Add user interface enhancements in app.py: introduce new selection options for site, sport, game type, contest size, and field strength, along with a clear data reset button, improving user experience and interaction within the application.

Implement conditional team stacking logic in app.py: add a check to ensure 'Stack' column is created only if it doesn't exist, enhancing the portfolio's team analysis functionality and preventing redundant calculations.

Add team stacking logic in app.py: implement a new feature to determine the most common team for players in the portfolio, enhancing team analysis capabilities and improving user insights into player distributions.

Update score cutoff values in app.py: increase the score_cutoff for name matching from 85 to 87 to enhance matching accuracy for portfolio and projections, ensuring better alignment with user expectations.

Update export file assignment logic in app.py: streamline the assignment of export_file by directly referencing display_frame based on user selection, improving clarity and consistency in data handling for export processes.

Refactor download options in app.py: comment out the previous download options logic for clarity, and implement a new selection mechanism for displaying either the portfolio or export base, enhancing user experience and functionality in data export processes.

Reset index of export base after adding new entries in app.py: ensure the DataFrame maintains a clean index by resetting it following the concatenation and duplicate removal process.

Refactor player statistics calculation in app.py: update references from working_frame to display_frame for improved clarity and consistency in player data processing, and add logic to drop duplicate entries in the export base upon addition.

Remove redundant assignment of display_frame in app.py: eliminate unnecessary line that sets display_frame to working_frame, streamlining the logic for frame selection based on user input.

Refactor trimming logic in app.py: streamline the portfolio trimming process by creating a copy of the working_frame before applying the trim function, and restore the display frame selection functionality for improved user experience.

Add info_columns_dict initialization in app.py: implement logic to store key metrics from working_frame in session state for improved data tracking, and refactor filtering logic to enhance clarity and maintainability of lineup processing.

Enhance name matching logic in app.py: improve clarity of output messages by specifying the source of matches for both portfolio and projections, and update projections DataFrame in session state with matched names for better data consistency.

Refactor portfolio reset functionality in app.py: modify the reset button logic to delete the working_frame from session state, ensuring a clearer reset process, and update working_frame initialization to consistently reference the origin_portfolio.

Adjust score cutoff values in app.py: lower the score_cutoff for name matching from 90 to 85 to improve matching flexibility, and update working_frame assignment in session state for clarity in portfolio reset functionality.

Add export dictionary initialization in app.py: implement logic to create an export_dict from csv_file, enhancing data handling for export operations while ensuring fallback for missing keys.

Update projection names handling in app.py: replace direct reference to projections DataFrame with session state for improved data consistency and clarity in name matching logic.

Refactor name matching logic in app.py: streamline the process of matching portfolio names to projection names by utilizing session state for improved clarity and efficiency, while enhancing the output messages for better user feedback.

Refactor map_dict handling in app.py: replace local map_dict variable with session state reference for improved consistency and clarity in data processing across various operations.

Enhance working_frame processing in app.py: add prediction and trimming logic to session state, ensuring maximum values are tracked for key metrics, improving data handling and analysis capabilities.