Update app.py to adjust column indices for player metrics in DraftKings and FanDuel sections, ensuring accurate data retrieval and enhancing the overall functionality of the application.

app.py

@@ -478,44 +478,44 @@ with tab3:
                 summary_df = pd.DataFrame({
                     'Metric': ['Min', 'Average', 'Max', 'STDdev'],
                     'Salary': [
-                        np.min(st.session_state.working_seed[:,6]),
-                        np.mean(st.session_state.working_seed[:,6]),
-                        np.max(st.session_state.working_seed[:,6]),
-                        np.std(st.session_state.working_seed[:,6])
+                        np.min(st.session_state.working_seed[:,9]),
+                        np.mean(st.session_state.working_seed[:,9]),
+                        np.max(st.session_state.working_seed[:,9]),
+                        np.std(st.session_state.working_seed[:,9])
                     ],
                     'Proj': [
-                        np.min(st.session_state.working_seed[:,7]),
-                        np.mean(st.session_state.working_seed[:,7]),
-                        np.max(st.session_state.working_seed[:,7]),
-                        np.std(st.session_state.working_seed[:,7])
+                        np.min(st.session_state.working_seed[:,10]),
+                        np.mean(st.session_state.working_seed[:,10]),
+                        np.max(st.session_state.working_seed[:,10]),
+                        np.std(st.session_state.working_seed[:,10])
                     ],
                     'Own': [
-                        np.min(st.session_state.working_seed[:,8]),
-                        np.mean(st.session_state.working_seed[:,8]),
-                        np.max(st.session_state.working_seed[:,8]),
-                        np.std(st.session_state.working_seed[:,8])
+                        np.min(st.session_state.working_seed[:,15]),
+                        np.mean(st.session_state.working_seed[:,15]),
+                        np.max(st.session_state.working_seed[:,15]),
+                        np.std(st.session_state.working_seed[:,15])
                     ]
                 })
             elif site_var == 'Fanduel':
                 summary_df = pd.DataFrame({
                     'Metric': ['Min', 'Average', 'Max', 'STDdev'],
                     'Salary': [
-                        np.min(st.session_state.working_seed[:,6]),
-                        np.mean(st.session_state.working_seed[:,6]),
-                        np.max(st.session_state.working_seed[:,6]),
-                        np.std(st.session_state.working_seed[:,6])
-                    ],
-                    'Proj': [
-                        np.min(st.session_state.working_seed[:,7]),
-                        np.mean(st.session_state.working_seed[:,7]),
-                        np.max(st.session_state.working_seed[:,7]),
-                        np.std(st.session_state.working_seed[:,7])
-                    ],
-                    'Own': [
                         np.min(st.session_state.working_seed[:,8]),
                         np.mean(st.session_state.working_seed[:,8]),
                         np.max(st.session_state.working_seed[:,8]),
                         np.std(st.session_state.working_seed[:,8])
+                    ],
+                    'Proj': [
+                        np.min(st.session_state.working_seed[:,9]),
+                        np.mean(st.session_state.working_seed[:,9]),
+                        np.max(st.session_state.working_seed[:,9]),
+                        np.std(st.session_state.working_seed[:,9])
+                    ],
+                    'Own': [
+                        np.min(st.session_state.working_seed[:,14]),
+                        np.mean(st.session_state.working_seed[:,14]),
+                        np.max(st.session_state.working_seed[:,14]),
+                        np.std(st.session_state.working_seed[:,14])
                     ]
                 })
 
@@ -535,9 +535,9 @@ with tab3:
         with tab1:
             if 'data_export_display' in st.session_state:
                 if site_var == 'Draftkings':
-                    player_columns = st.session_state.data_export_display.iloc[:, :6]
+                    player_columns = st.session_state.data_export_display.iloc[:, :10]
                 elif site_var == 'Fanduel':
-                    player_columns = st.session_state.data_export_display.iloc[:, :6]
+                    player_columns = st.session_state.data_export_display.iloc[:, :9]
                 
                 # Flatten the DataFrame and count unique values
                 value_counts = player_columns.values.flatten().tolist()
@@ -571,9 +571,9 @@ with tab3:
         with tab2:
             if 'working_seed' in st.session_state:
                 if site_var == 'Draftkings':
-                    player_columns = st.session_state.working_seed[:, :6]
+                    player_columns = st.session_state.working_seed[:, :10]
                 elif site_var == 'Fanduel':
-                    player_columns = st.session_state.working_seed[:, :6]
+                    player_columns = st.session_state.working_seed[:, :9]
                 
                 # Flatten the DataFrame and count unique values
                 value_counts = player_columns.flatten().tolist()