fixed min/max/std stuff for summary frame

app.py

@@ -297,27 +297,50 @@ with tab2:
         with st.container():
             if 'working_seed' in st.session_state:
                 # Create a new dataframe with summary statistics
-                summary_df = pd.DataFrame({
-                    'Metric': ['Min', 'Average', 'Max', 'STDdev'],
-                    'Salary': [
-                        st.session_state.working_seed['salary'].min(),
-                        st.session_state.working_seed['salary'].mean(),
-                        st.session_state.working_seed['salary'].max(),
-                        st.session_state.working_seed['salary'].std()
-                    ],
-                    'Proj': [
-                        st.session_state.working_seed['proj'].min(),
-                        st.session_state.working_seed['proj'].mean(),
-                        st.session_state.working_seed['proj'].max(),
-                        st.session_state.working_seed['proj'].std()
-                    ],
-                    'Own': [
-                        st.session_state.working_seed['Own'].min(),
-                        st.session_state.working_seed['Own'].mean(),
-                        st.session_state.working_seed['Own'].max(),
-                        st.session_state.working_seed['Own'].std()
-                    ]
-                })
+                if site_var1 == 'Draftkings':
+                    summary_df = pd.DataFrame({
+                        'Metric': ['Min', 'Average', 'Max', 'STDdev'],
+                        'Salary': [
+                            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])
+                        ]
+                    })
+                elif site_var1 == 'Fanduel':
+                    summary_df = pd.DataFrame({
+                        'Metric': ['Min', 'Average', 'Max', 'STDdev'],
+                        'Salary': [
+                            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[:,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[:,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])
+                        ]
+                    })
 
                 # Set the index of the summary dataframe as the "Metric" column
                 summary_df = summary_df.set_index('Metric')