Update app.py

app.py

@@ -246,35 +246,43 @@ with tab1:
         min_var1 = st.slider("Is there a certain TOI range you want to view?", 0, 50, (0, 50), key='min_var1')
     
     with col2:
+        working_data = gamelog_table
         if split_var1 == 'Season Logs':
             choose_cols = st.container()
             with choose_cols:
                 choose_disp = st.multiselect('Which stats would you like to view?', options = season_data_cols, default = season_data_cols, key='col_display')
             disp_stats = basic_season_cols + choose_disp
             display = st.container()
-            gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date]
-            gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date]
-            gamelog_table = gamelog_table[gamelog_table['TOI'] >= min_var1[0]]
-            gamelog_table = gamelog_table[gamelog_table['TOI'] <= min_var1[1]]
-            gamelog_table = gamelog_table[gamelog_table['Team'].isin(team_var1)]
-            gamelog_table = gamelog_table[gamelog_table['Player'].isin(player_var1)]
-            season_long_table = seasonlong_build(gamelog_table)
+            working_data = working_data[working_data['Date'] >= low_date]
+            working_data = working_data[working_data['Date'] <= high_date]
+            working_data = working_data[working_data['TOI'] >= min_var1[0]]
+            working_data = working_data[working_data['TOI'] <= min_var1[1]]
+            working_data = working_data[working_data['Team'].isin(team_var1)]
+            working_data = working_data[working_data['Player'].isin(player_var1)]
+            season_long_table = seasonlong_build(working_data)
             season_long_table = season_long_table.set_index('Player')
             season_long_table_disp = season_long_table.reindex(disp_stats,axis="columns")
             display.dataframe(season_long_table_disp.style.format(precision=2), height=750, use_container_width = True)  
+            st.download_button(
+                    label="Export seasonlogs Model",
+                    data=convert_df_to_csv(season_long_table),
+                    file_name='Seasonlogs_NHL_View.csv',
+                    mime='text/csv',
+            )
             
         elif split_var1 == 'Gamelogs':
             choose_cols = st.container()
             with choose_cols:
                 choose_disp = st.multiselect('Which stats would you like to view?', options = data_cols, default = data_cols, key='col_display')
-            disp_stats = basic_cols + choose_disp
-            gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date]
-            gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date]
-            gamelog_table = gamelog_table[gamelog_table['TOI'] >= min_var1[0]]
-            gamelog_table = gamelog_table[gamelog_table['TOI'] <= min_var1[1]]
-            gamelog_table = gamelog_table[gamelog_table['Team'].isin(team_var1)]
-            gamelog_table = gamelog_table[gamelog_table['Player'].isin(player_var1)]
-            gamelog_table = gamelog_table.reset_index(drop=True)
+            gamelog_disp_stats = basic_cols + choose_disp
+            working_data = working_data[working_data['Date'] >= low_date]
+            working_data = working_data[working_data['Date'] <= high_date]
+            working_data = working_data[working_data['TOI'] >= min_var1[0]]
+            working_data = working_data[working_data['TOI'] <= min_var1[1]]
+            working_data = working_data[working_data['Team'].isin(team_var1)]
+            working_data = working_data[working_data['Player'].isin(player_var1)]
+            working_data = working_data.reset_index(drop=True)
+            gamelog_data = working_data.reindex(gamelog_disp_stats,axis="columns")
             display = st.container()
         
             bottom_menu = st.columns((4, 1, 1))
@@ -282,7 +290,7 @@ with tab1:
                 batch_size = st.selectbox("Page Size", options=[25, 50, 100])
             with bottom_menu[1]:
                 total_pages = (
-                    int(len(gamelog_table) / batch_size) if int(len(gamelog_table) / batch_size) > 0 else 1
+                    int(len(gamelog_data) / batch_size) if int(len(gamelog_data) / batch_size) > 0 else 1
                 )
                 current_page = st.number_input(
                     "Page", min_value=1, max_value=total_pages, step=1
@@ -291,9 +299,15 @@ with tab1:
                 st.markdown(f"Page **{current_page}** of **{total_pages}** ")
             
             
-            pages = split_frame(gamelog_table, batch_size)
+            pages = split_frame(gamelog_data, batch_size)
             # pages = pages.set_index('Player')
             display.dataframe(data=pages[current_page - 1].style.format(precision=2), height=500, use_container_width=True)
+            st.download_button(
+                    label="Export gamelogs Model",
+                    data=convert_df_to_csv(gamelog_data),
+                    file_name='Gamelogs_NBA_View.csv',
+                    mime='text/csv',
+            )
             
 with tab2:
     col1, col2 = st.columns([1, 9])