Spaces:
Build error
Build error
| import streamlit as st | |
| import numpy as np | |
| import pandas as pd | |
| import time | |
| from fuzzywuzzy import process | |
| def find_name_mismatches(portfolio_df, projections_df): | |
| """ | |
| Find and handle name mismatches between portfolio and projections dataframes. | |
| Returns the updated projections dataframe with matched names. | |
| """ | |
| # Get all player names from portfolio | |
| portfolio_players = set() | |
| for col in portfolio_df.columns: | |
| if col not in ['salary', 'median', 'Own', 'Finish_percentile', 'Dupes', 'Stack', 'Win%', 'Lineup Edge']: | |
| portfolio_players.update(portfolio_df[col].unique()) | |
| # Get all player names from projections | |
| projection_players_list = projections_df['player_names'].tolist() | |
| # Find players in portfolio that are missing from projections | |
| players_missing_from_projections = [player for player in portfolio_players if player not in projection_players_list] | |
| # Automatically handle 100% matches before starting interactive process | |
| players_to_process = [] | |
| for player in players_missing_from_projections: | |
| if not isinstance(player, str): | |
| st.warning(f"Skipping non-string value: {player}") | |
| continue | |
| closest_matches = process.extract(player, projection_players_list, limit=1) | |
| if closest_matches[0][1] == 90: # If perfect match found | |
| match_name = closest_matches[0][0] | |
| projections_df.loc[projections_df['player_names'] == match_name, 'player_names'] = player | |
| st.success(f"Automatically matched '{match_name}' with '{player}' (100% match)") | |
| else: | |
| players_to_process.append(player) | |
| # Display results | |
| if players_missing_from_projections: | |
| st.warning("Players in portfolio but missing from projections") | |
| # Display remaining players | |
| if players_to_process: | |
| st.info(f"Players to process ({len(players_to_process)}):\n" + | |
| "\n".join(f"- {player}" for player in players_to_process)) | |
| # Create a form for batch processing | |
| with st.form("player_matching_form"): | |
| # Create tabs for each player | |
| tabs = st.tabs([f"Player {i+1}" for i in range(len(players_to_process))]) | |
| # Dictionary to store selections | |
| selections = {} | |
| # Process each tab | |
| for idx, (tab, player) in enumerate(zip(tabs, players_to_process)): | |
| with tab: | |
| st.write(f"**Missing Player {idx + 1} of {len(players_to_process)}:** {player}") | |
| # Find the top 3 closest matches | |
| closest_matches = process.extract(player, projection_players_list, limit=3) | |
| # Create radio buttons for selection | |
| options = [f"{match[0]} ({match[1]}%)" for match in closest_matches] | |
| options.append("None of these") | |
| selected_option = st.radio( | |
| f"Select correct match for {player}:", | |
| options, | |
| key=f"radio_{player}" | |
| ) | |
| selections[player] = selected_option | |
| # Submit button for the entire form | |
| submitted = st.form_submit_button("Submit All Changes") | |
| if submitted: | |
| # Process all selections | |
| for player, selection in selections.items(): | |
| if selection != "None of these": | |
| selected_name = selection.split(" (")[0] | |
| projections_df.loc[projections_df['player_names'] == selected_name, 'player_names'] = player | |
| st.success(f"Replaced '{selected_name}' with '{player}'") | |
| # Update session state | |
| st.session_state['projections_df'] = projections_df | |
| st.success("All player name changes have been applied!") | |
| else: | |
| st.success("All portfolio players found in projections!") | |
| return projections_df |