Refactor app.py: Simplify data export handling by removing unnecessary DataFrame conversion for session state display. This change enhances performance and maintains consistency in data representation across player selections.

app.py

@@ -208,7 +208,7 @@ with tab2:
                     st.session_state.working_seed = st.session_state.working_seed
                     if player_var1 == 'Specific Players':
                         st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+                    st.session_state.data_export_display = st.session_state.working_seed[0:lineup_num_var]
                     export_column_var = 8
                 elif 'working_seed' not in st.session_state:
                     if slate_var1 == 'Main Slate':
@@ -226,7 +226,7 @@ with tab2:
                 
                     if player_var1 == 'Specific Players':
                         st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+                    st.session_state.data_export_display = st.session_state.working_seed[0:lineup_num_var]
                     export_column_var = 8
                 data_export = st.session_state.data_export_display.copy()
                 for col in range(export_column_var):
@@ -237,7 +237,7 @@ with tab2:
                     st.session_state.working_seed = st.session_state.working_seed
                     if player_var1 == 'Specific Players':
                         st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+                    st.session_state.data_export_display = st.session_state.working_seed[0:lineup_num_var]
                     export_column_var = 9
                 elif 'working_seed' not in st.session_state:
                     if slate_var1 == 'Main Slate':
@@ -255,7 +255,7 @@ with tab2:
 
                     if player_var1 == 'Specific Players':
                         st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+                    st.session_state.data_export_display = st.session_state.working_seed[0:lineup_num_var]
                     export_column_var = 9
                 data_export = st.session_state.data_export_display.copy()
                 for col in range(export_column_var):