Fix 'Team_Total' column mapping in app.py to correctly reference 'Player' instead of 'Team'. This adjustment ensures accurate data retrieval for team totals, enhancing the integrity of player selection metrics.

Enhance player data management in app.py by adding 'Team_Total' and 'Opp_Total' columns to the lineup. Updated DataFrame structures and quick fill options to incorporate these new metrics, improving the clarity and depth of player selection information.

Handle potential errors when inserting 'Order' column in roo_data within app.py. Added a try-except block to ensure compatibility with non-integer values, enhancing data integrity during player selection.

Refactor Handbuilder section in app.py to include a slate selection dropdown, allowing users to filter player data based on slate type. Updated team filtering logic to utilize the filtered handbuild_roo dataset for improved accuracy in player selection.

Update quick fill options in app.py to include detailed descriptions for player selection ranges. This change enhances clarity for users by specifying the player order ranges associated with each option.

Enhance player selection logic in app.py by modifying the wrap option to include the first three and last two players based on order. This change improves the flexibility and efficiency of lineup management.

Add quick fill options in app.py to streamline player selection for lineups. Implemented logic to auto-fill eligible players based on team, size, and order preferences, enhancing user experience and efficiency in lineup management.

Add 'Opp' column to roo_data in app.py for enhanced player matchup information. Adjusted column order to improve data organization and clarity in the lineup summary.

Refactor salary display logic in app.py by removing JavaScript dependency for screen width and simplifying column layout. This change enhances the user experience by ensuring consistent presentation of salary information across all devices.

Refactor mobile layout in app.py to enhance salary display by adjusting column alignment and improving HTML formatting. This change ensures consistent presentation of per player salary and leftover amounts across different screen sizes.

Refactor HTML styling in app.py for salary display to improve alignment and visual consistency. Adjusted vertical alignment and margin properties for better presentation of player salary and leftover amounts in the lineup summary.

Implement responsive column layout in app.py based on screen width to enhance user experience on mobile devices. Default to desktop layout if JavaScript fails to retrieve screen width.

Limit displayed summary rows to the top 10 in app.py for improved clarity and user experience in the lineup summary. Adjusted labels for better context on salary and leftover amounts.

Implement conditional logic for per player salary display in app.py to handle cases with filled lineups. This enhancement ensures accurate salary calculations and improves user clarity in the lineup summary.

Refactor salary display in app.py to utilize HTML for improved formatting and alignment, enhancing visual clarity and user experience in the lineup summary.

Refactor salary display in app.py to use HTML for improved formatting and alignment. This change enhances visual clarity by presenting salary and median values in a more structured manner, contributing to a better user experience in the lineup summary.

Enhance salary display logic in app.py by introducing conditional formatting for total salary. If the total salary exceeds the limit, it now displays an error message, improving user clarity in the lineup summary.

Update label in app.py from "Rem$ Player" to "Per Player" to enhance clarity in the salary display, improving user understanding in the lineup summary.

Update markdown formatting in app.py to improve the display of remaining salary per player, enhancing visual clarity with a minor adjustment to the label for better user engagement in the lineup summary.

Adjust column layout in app.py to improve the display of player cost per player, enhancing visual clarity with a markdown format for better user engagement in the lineup summary.

Update markdown formatting in app.py to enhance the display of salary, median, and ownership percentage, improving clarity and user engagement in the lineup summary.

Update markdown labels in app.py for salary, median, and ownership percentage display to improve clarity and user understanding in the lineup summary.

Enhance lineup summary display in app.py by expanding the layout to three columns. Introduced a markdown format for displaying total salary, median, and ownership percentages, improving visual clarity and user engagement.

Refine totals display in app.py by ensuring consistent rounding for median and ownership values. This update enhances clarity in the lineup summary, improving the overall user experience.

Update player cost display in app.py to round values for clarity and replace dataframe with a summary of total salary and statistics. This change enhances the user experience by providing a more concise overview of lineup performance.

Update lineup display in app.py to refine summary row presentation by including only 'Salary', 'Median', and 'Own%' columns. Introduced a two-column layout for displaying player cost per player alongside the updated dataframe, enhancing user experience in lineup management.

Refactor player selection logic in app.py to filter eligible players based on their 'Order' value before applying auto-fill options. This change improves the accuracy of selected players for lineup management, ensuring only valid entries are considered.

Refactor Quick Fill Options in app.py by simplifying the layout of the auto-fill selections. This change enhances the user interface by removing unnecessary columns, streamlining the quick fill process for better usability in lineup management.

Enhance player selection logic in app.py by adding functionality to automatically fill eligible lineup slots based on selected players. This update improves lineup management by preventing duplicates and ensuring compliance with position limits, while also maintaining the existing quick fill options.

Refactor Quick Fill Options in app.py by reintroducing the feature with improved layout and logic for auto-filling players based on team selection and size. This enhances user experience in lineup management.

Add team filter and quick fill options in app.py to enhance lineup management. Introduced UI elements for auto-filling players based on selected team and size, improving user experience and efficiency in lineup building.

Refactor lineup display in app.py by removing '2x%' column from background gradient styling, enhancing clarity in player data presentation and maintaining focus on key statistics.

Remove '2x%' column from display in Handbuilder tab of app.py to streamline player data presentation and enhance clarity in lineup management.

Remove specific CSS styling for text input height in app.py to streamline the user interface and maintain consistency across components.

Adjust CSS styling in app.py to set a specific height for text input fields within the Handbuilder tab, enhancing the visual consistency of the user interface.

Refactor lineup display logic in app.py to ensure that the player data is only processed when the filled lineup is not empty. This change enhances the efficiency of the display logic and maintains clarity in the representation of player statistics.

Update Handbuilder lineup DataFrame in app.py to include '2x%' column, enhancing player data management and display. Adjust related logic for player selection and summary calculations to ensure accurate representation of player statistics, improving user experience and clarity.

Update subheader in Handbuilder tab of app.py to "Lineup Build" for improved clarity and context in lineup management.

Update Handbuilder tab in app.py to replace empty string values with NaN for 'Order', 'Salary', 'Median', and 'Own%' columns in the lineup DataFrame. Adjust background gradient logic for improved visual representation of player data, enhancing clarity and user experience.

Enhance DataFrame display in Handbuilder tab of app.py by applying background gradients to player selection and lineup tables. This improves visual clarity and user experience when reviewing player data.

Implement single-row selection for lineup removal in Handbuilder tab of app.py, allowing users to easily remove players from the lineup. Update DataFrame display logic to enhance user interaction and streamline lineup management.

Comment out player eligibility filtering in Handbuilder tab of app.py to temporarily disable player selection logic, allowing for further testing and adjustments without affecting current functionality.

Update Handbuilder lineup DataFrame in app.py to include 'Order' column for improved player management and display. Adjust related logic to ensure consistent handling of player data across the application, enhancing clarity and user experience.

Enhance lineup display in Handbuilder tab of app.py by implementing an explicit order for player slots. Update DataFrame to show filled and unfilled slots clearly, and adjust summary calculations to ensure accurate representation of total salary, median, and ownership percentage. This improves user experience and data clarity.

Refactor player selection logic in Handbuilder tab of app.py to improve eligibility checks based on position limits. Update the DataFrame to include a 'Slot' column for better lineup management and ensure players are only added to available positions, enhancing user experience and data integrity.

Add 'Position' column to summary row in Handbuilder tab of app.py to provide a comprehensive overview of player data, enhancing clarity and user experience.

Implement position limits and filtering logic in Handbuilder tab of app.py to manage player selection more effectively. This update enhances lineup management by preventing selection of players whose positions have reached their maximum count, improving user experience.

Add position limits and filtering for player selection in Handbuilder tab of app.py. Implement logic to exclude players whose positions have reached their maximum count, enhancing lineup management and user experience.

Refine player selection DataFrame in Handbuilder tab of app.py by adding duplicate removal based on 'Player' and 'Team', ensuring data integrity and enhancing user experience.

Update player selection DataFrame in Handbuilder tab of app.py to remove duplicate entries based on 'Player' and 'Team', enhancing data integrity and improving user experience.