Add custom tab styling to improve UI aesthetics and user experience

Reorder NBA and NFL sport selection radio button options

Refactor Range of Outcomes tab layout and improve UI organization

Restore duplicate player removal for NBA and NFL projections

Temporarily disable duplicate player removal for NBA projections

Set Player column as index for NBA and NFL projection views

Enhance view selection info text for better user understanding

Refactor Range of Outcomes tab layout and improve data selection workflow

Update projection view columns to include Salary for NBA and NFL

Add view selection feature for NBA and NFL projections

Improve error handling for timestamp retrieval in app.py. Added nested try-except blocks to ensure fallback options for NFL timestamp acquisition, enhancing robustness and preventing application crashes due to missing data.

Refactor app.py to improve error handling for timestamp retrieval in NFL and NBA datasets. Enhanced the robustness of data processing by adding nested try-except blocks to ensure fallback options for missing timestamps, thereby preventing potential application crashes and improving data integrity.

Enhance app.py with error handling for database queries and data retrieval. Added try-except blocks to ensure robustness when fetching player data from NFL and NBA datasets, preventing application crashes due to missing data. This update improves data integrity and user experience by providing fallback options for empty datasets.

Enhance app.py to calculate 'salary' for CPT projections in NFL. Added a new calculation for 'salary' by dividing 'Salary' by 1.5, improving the accuracy of player salary projections based on sport selection.

Refactor app.py to ensure unique player entries across multiple DataFrames. Removed duplicate player entries in nfl_dk_sd_raw, nfl_fd_sd_raw, display_Proj, and display_baselines DataFrames by implementing drop_duplicates method for 'Player'. This enhancement improves data integrity and consistency in player projections.

Refactor app.py to remove duplicate player entries in NFL datasets. Added drop_duplicates method for 'Player' in both nfl_dk_sd_raw and nfl_fd_sd_raw DataFrames, enhancing data integrity and ensuring unique player projections.

Refactor app.py to remove redundant index setting for 'Player' in display_Proj DataFrame. This change simplifies the data processing logic and enhances readability of the code.

Refactor app.py to update player ID mapping for NBA and NFL datasets. Changed key from 'player_id' to 'Player' in the dictionary creation for improved data consistency and accuracy in player projections.

Refactor sport selection in app.py to change the order of options in radio buttons for loading and optimizing data from 'NBA, NFL' to 'NFL, NBA'. This adjustment improves user experience by prioritizing NFL in the selection process.

Enhance app.py to improve timestamp retrieval for NBA and NFL datasets. Added error handling to fallback on alternative data sources if primary timestamps are unavailable, ensuring robustness in data processing for player projections.

Refactor app.py to conditionally calculate 'CPT_Salary' and 'flex_proj' salaries based on sport selection (NBA or NFL). This update enhances the accuracy of player projections by applying different salary multipliers for each sport, improving the overall functionality of the application.

Refactor app.py to include 'player_id' in the raw_display DataFrame. This change enhances data structure for player projections, ensuring better integration with subsequent data processing and analysis.

Enhance app.py to support NBA and NFL player projections with distinct formatting. Introduced nba_player_roo_format and nfl_player_roo_format for improved data display based on sport selection. Updated dataframe rendering logic to conditionally format projections based on the selected sport, ensuring a more tailored user experience.

Refactor app.py to replace Google Sheets integration with MongoDB for data retrieval. Updated data loading functions to support NBA and NFL datasets, adjusted caching mechanisms, and streamlined user interface for sport selection. Removed deprecated code related to Google Sheets and improved data handling for player projections.

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