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DFS_Portfolio_Manager / global_func

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2 contributors

History: 72 commits

James McCool

Update preset label in app.py for clarity and consistency

84a7686 7 days ago

clean_player_name.py

423 Bytes

Initial Commit 3 months ago
distribute_preset.py

2.04 kB

Update preset label in app.py for clarity and consistency 7 days ago
find_csv_mismatches.py

4.28 kB

Initial Commit 3 months ago
find_name_mismatches.py

4.36 kB

Initial Commit 3 months ago
get_portfolio_names.py

864 Bytes

Add portfolio name extraction and matching in app.py: implement a new function to retrieve unique player names from the portfolio, enhance name matching logic, and update session state with matched names for improved data consistency and analysis. about 1 month ago
highlight_rows.py

971 Bytes

Initial Commit 3 months ago
large_field_preset.py

1.43 kB

Refactor large_field_preset function to streamline player removal logic by eliminating unnecessary iterations and simplifying the exposure tracking process. Ensure sufficient lineups are generated before finalizing selections, enhancing overall efficiency and accuracy. 7 days ago
load_csv.py

683 Bytes

Initial Commit 3 months ago
load_dk_fd_file.py

1.33 kB

Refactor file type checks in load_file.py and load_ss_file.py: streamline file extension validation using endswith method for improved readability. Update app.py to handle salary conversion more robustly by removing unnecessary exception handling. 24 days ago
load_file.py

1.26 kB

Remove unnamed columns from uploaded DataFrame in load_file.py: enhance data cleanliness by dropping columns with 'Unnamed' in their names before further processing. 9 days ago
load_ss_file.py

1.14 kB

Refactor file type checks in load_file.py and load_ss_file.py: streamline file extension validation using endswith method for improved readability. Update app.py to handle salary conversion more robustly by removing unnecessary exception handling. 24 days ago
optimize_lineup.py

3.19 kB

Initial Commit 3 months ago
predict_dupes.py

17.8 kB

Update salary input limits in app.py: increase the maximum acceptable salary from 60,000 to 100,000 to accommodate a wider range of salary options for users. Adjust conditional checks in predict_dupes.py to use 'elif' for improved clarity in type_var evaluations. 27 days ago
small_field_preset.py

1.47 kB

Enhance small_field_preset and large_field_preset functions to accept an additional parameter for excluded columns, improving filtering capabilities and lineup accuracy. Update app.py to reflect these changes in preset selections. 7 days ago
trim_portfolio.py

1.37 kB

Fix calculation of current ownership type maximum in trim_portfolio.py to use the correct row's own type value, improving accuracy in portfolio trimming logic. 22 days ago