added some filters to lineups

app.py

@@ -146,7 +146,7 @@ dk_lineups = init_DK_lineups()
 fd_lineups = init_FD_lineups()
 t_stamp = f"Last Update: " + str(timestamp) + f" CST"
 
-tab1, tab2 = st.tabs(['Range of Outcomes', 'Uploads and Info'])
+tab1, tab2 = st.tabs(['Range of Outcomes', 'Optimals'])
 
 with tab1:
 
@@ -222,6 +222,9 @@ with tab2:
         site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'))
         if site_var1 == 'Draftkings':
             raw_baselines = dk_raw
+            # Get the minimum and maximum ownership values from dk_lineups
+            min_own = dk_lineups['Own'].min()
+            max_own = dk_lineups['Own'].max()
             column_names = dk_columns
             
             player_var1 = st.radio("Do you want a frame with specific Players?", ('Full Slate', 'Specific Players'), key='player_var1')
@@ -229,16 +232,31 @@ with tab2:
                     player_var2 = st.multiselect('Which players do you want?', options = dk_raw['Player'].unique())
             elif player_var1 == 'Full Slate':
                     player_var2 = dk_raw.Player.values.tolist()
+            
+            own_var_low, own_var_high = st.slider("Select ownership range", 
+                                  min_value=float(min_own), 
+                                  max_value=float(max_own), 
+                                  value=(float(min_own), float(max_own)), 
+                                  step=10)
                     
         elif site_var1 == 'Fanduel':
             raw_baselines = fd_raw
+            min_own = fd_lineups['Own'].min()
+            max_own = fd_lineups['Own'].max()
             column_names = fd_columns
             
             player_var1 = st.radio("Do you want a frame with specific Players?", ('Full Slate', 'Specific Players'), key='player_var1')
             if player_var1 == 'Specific Players':
-                    player_var2 = st.multiselect('Which players do you want?', options = dk_raw['Player'].unique())
+                    player_var2 = st.multiselect('Which players do you want?', options = fd_raw['Player'].unique())
             elif player_var1 == 'Full Slate':
-                    player_var2 = dk_raw.Player.values.tolist()
+                    player_var2 = fd_raw.Player.values.tolist()
+            
+            own_var_low, own_var_high = st.slider("Select ownership range", 
+                                  min_value=float(min_own), 
+                                  max_value=float(max_own), 
+                                  value=(float(min_own), float(max_own)), 
+                                  step=10)
+                    
         
 
         if st.button("Prepare data export", key='data_export'):
@@ -254,19 +272,47 @@ with tab2:
         if site_var1 == 'Draftkings':
             if 'working_seed' in st.session_state:
                 st.session_state.working_seed = st.session_state.working_seed
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] >= own_var_low]
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] <= own_var_high]
+                # Create a mask to check if any column contains a player from player_var2
+                player_mask = st.session_state.working_seed.apply(lambda row: any(player in str(cell) for player in player_var2 for cell in row), axis=1)
+                
+                # Apply the mask to filter the DataFrame
+                st.session_state.working_seed = st.session_state.working_seed[player_mask]
                 st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
             elif 'working_seed' not in st.session_state:
                 st.session_state.working_seed = dk_lineups.copy()
                 st.session_state.working_seed = st.session_state.working_seed
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] >= own_var_low]
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] <= own_var_high]
+                # Create a mask to check if any column contains a player from player_var2
+                player_mask = st.session_state.working_seed.apply(lambda row: any(player in str(cell) for player in player_var2 for cell in row), axis=1)
+                
+                # Apply the mask to filter the DataFrame
+                st.session_state.working_seed = st.session_state.working_seed[player_mask]
                 st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
             
         elif site_var1 == 'Fanduel':
             if 'working_seed' in st.session_state:
                 st.session_state.working_seed = st.session_state.working_seed
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] >= own_var_low]
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] <= own_var_high]
+                # Create a mask to check if any column contains a player from player_var2
+                player_mask = st.session_state.working_seed.apply(lambda row: any(player in str(cell) for player in player_var2 for cell in row), axis=1)
+                
+                # Apply the mask to filter the DataFrame
+                st.session_state.working_seed = st.session_state.working_seed[player_mask]
                 st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
             elif 'working_seed' not in st.session_state:
                 st.session_state.working_seed = fd_lineups.copy()
                 st.session_state.working_seed = st.session_state.working_seed
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] >= own_var_low]
+                st.session_state.working_seed = st.session_state.working_seed[st.session_state.working_seed['Own'] <= own_var_high]
+                # Create a mask to check if any column contains a player from player_var2
+                player_mask = st.session_state.working_seed.apply(lambda row: any(player in str(cell) for player in player_var2 for cell in row), axis=1)
+                
+                # Apply the mask to filter the DataFrame
+                st.session_state.working_seed = st.session_state.working_seed[player_mask]
                 st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
                 
         with st.container():