Refactor data loading and filtering options in app.py, introducing new radio buttons for site, slate type, and position group selection, enhancing user interaction and data management capabilities.

app.py

@@ -149,14 +149,25 @@ with tab1:
 with tab2:
     st.title("Player ROO")
     with st.expander("Info and Filters"):
-        site_var = st.radio("Select site", ["Draftkings", "Fanduel"])
-        if site_var == "Draftkings":
-            display_data = sd_roo_data[sd_roo_data['site'] == 'Draftkings']
-            display_data = display_data[display_data['slate'] == 'DK SD1']
-        elif site_var == "Fanduel":
-            display_data = sd_roo_data[sd_roo_data['site'] == 'Fanduel']
-            display_data = display_data[display_data['slate'] == 'FD SD1']
+        col1, col2, col3, col4, col5 = st.columns([3, 3, 3, 3, 3])
+        with col1:
+            if st.button("Load/Reset Data", key='reset1'):
+                st.cache_data.clear()
+                roo_data, sd_roo_data, scoring_percentages = init_baselines()
+                hold_display = roo_data
+        with col2:
+            site_var2 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'), key='site_var2')
+        with col3:
+            slate_type_var2 = st.radio("Which slate type are you loading?", ('Regular', 'Showdown'), key='slate_type_var2')
+        with col4:
+            slate_var2 = st.radio("Which slate data are you loading?", ('Main', 'Secondary', 'Auxiliary'), key='slate_var2')
+        with col5:
+            pos_var2 = st.radio("Which position group would you like to view?", ('All', 'Pitchers', 'Hitters'), key='pos_var2')
     
+    if slate_type_var2 == 'Regular':
+        display_data = roo_data
+    elif slate_type_var2 == 'Showdown':
+        display_data = sd_roo_data
     display_data = display_data.drop(columns=['site', 'slate', 'version', 'timestamp'])
     if view_var == "Simple":
         display_data = display_data[['Player', 'Position', 'Salary', 'Median', 'Ceiling', 'Own']]
@@ -170,36 +181,37 @@ with tab3:
             st.cache_data.clear()
             roo_data, sd_roo_data, scoring_percentages = init_baselines()
             hold_display = roo_data
-            dk_lineups = init_DK_lineups()
-            fd_lineups = init_FD_lineups()
+            dk_lineups = init_DK_lineups('Main')
+            fd_lineups = init_FD_lineups('Main')
             for key in st.session_state.keys():
                 del st.session_state[key]
-              
-        slate_var1 = st.radio("Which data are you loading?", ('Regular', 'Showdown'))
         
-        site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'))
-        if slate_var1 == 'Regular':
-            if site_var1 == 'Draftkings':
-                dk_lineups = init_DK_lineups()
-            elif site_var1 == 'Fanduel':
-                fd_lineups = init_FD_lineups()
-        elif slate_var1 == 'Showdown':
-            if site_var1 == 'Draftkings':
-                dk_lineups = init_DK_lineups()
-            elif site_var1 == 'Fanduel':
-                fd_lineups = init_FD_lineups()
+        site_var3 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'), key='site_var3')
+        slate_type_var3 = st.radio("Which slate type are you loading?", ('Regular', 'Showdown'), key='slate_type_var3')
+        slate_var3 = st.radio("Which slate data are you loading?", ('Main', 'Secondary', 'Auxiliary'), key='slate_var3')
+
+        if slate_type_var3 == 'Regular':
+            if site_var3 == 'Draftkings':
+                dk_lineups = init_DK_lineups(slate_var3)
+            elif site_var3 == 'Fanduel':
+                fd_lineups = init_FD_lineups(slate_var3)
+        elif slate_type_var3 == 'Showdown':
+            if site_var3 == 'Draftkings':
+                dk_lineups = init_DK_lineups(slate_var3)
+            elif site_var3 == 'Fanduel':
+                fd_lineups = init_FD_lineups(slate_var3)
         lineup_num_var = st.number_input("How many lineups do you want to display?", min_value=1, max_value=1000, value=150, step=1)
         
-        if slate_var1 == 'Regular':
+        if slate_type_var3 == 'Regular':
                 raw_baselines = roo_data
-        elif slate_var1 == 'Showdown':
+        elif slate_type_var3 == 'Showdown':
             raw_baselines = sd_roo_data
         
-        if site_var1 == 'Draftkings':
-            if slate_var1 == 'Regular':
+        if site_var3 == 'Draftkings':
+            if slate_type_var3 == 'Regular':
                 ROO_slice = raw_baselines[raw_baselines['Site'] == 'Draftkings']
                 player_salaries = dict(zip(ROO_slice['Player'], ROO_slice['Salary']))
-            elif slate_var1 == 'Showdown':
+            elif slate_type_var3 == 'Showdown':
                 player_salaries = dict(zip(raw_baselines['Player'], raw_baselines['Salary']))
             # Get the minimum and maximum ownership values from dk_lineups
             min_own = np.min(dk_lineups[:,8])
@@ -212,12 +224,12 @@ with tab3:
             elif player_var1 == 'Full Slate':
                     player_var2 = raw_baselines.Player.values.tolist()
                     
-        elif site_var1 == 'Fanduel':
+        elif site_var3 == 'Fanduel':
             raw_baselines = hold_display
-            if slate_var1 == 'Regular':
+            if slate_type_var3 == 'Regular':
                 ROO_slice = raw_baselines[raw_baselines['Site'] == 'Fanduel']
                 player_salaries = dict(zip(ROO_slice['Player'], ROO_slice['Salary']))
-            elif slate_var1 == 'Showdown':
+            elif slate_type_var3 == 'Showdown':
                 player_salaries = dict(zip(raw_baselines['Player'], raw_baselines['Salary']))
             min_own = np.min(fd_lineups[:,8])
             max_own = np.max(fd_lineups[:,8])
@@ -231,10 +243,10 @@ with tab3:
 
         if st.button("Prepare data export", key='data_export'):
             data_export = st.session_state.working_seed.copy()
-            # if site_var1 == 'Draftkings':
+            # if site_var3 == 'Draftkings':
             #     for col_idx in range(6):
             #         data_export[:, col_idx] = np.array([id_dict.get(player, player) for player in data_export[:, col_idx]])
-            # elif site_var1 == 'Fanduel':
+            # elif site_var3 == 'Fanduel':
             #     for col_idx in range(6):
             #         data_export[:, col_idx] = np.array([id_dict.get(player, player) for player in data_export[:, col_idx]])
             st.download_button(
@@ -244,7 +256,7 @@ with tab3:
                 mime='text/csv',
             )
         
-    if site_var1 == 'Draftkings':
+    if site_var3 == 'Draftkings':
         if 'working_seed' in st.session_state:
             st.session_state.working_seed = st.session_state.working_seed
             if player_var1 == 'Specific Players':
@@ -261,7 +273,7 @@ with tab3:
                 st.session_state.working_seed = dk_lineups.copy()
             st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
         
-    elif site_var1 == 'Fanduel':
+    elif site_var3 == 'Fanduel':
         if 'working_seed' in st.session_state:
             st.session_state.working_seed = st.session_state.working_seed
             if player_var1 == 'Specific Players':
@@ -279,10 +291,10 @@ with tab3:
             st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
 
     export_file = st.session_state.data_export_display.copy()
-    # if site_var1 == 'Draftkings':
+    # if site_var3 == 'Draftkings':
     #     for col_idx in range(6):
     #         export_file.iloc[:, col_idx] = export_file.iloc[:, col_idx].map(id_dict)
-    # elif site_var1 == 'Fanduel':
+    # elif site_var3 == 'Fanduel':
     #     for col_idx in range(6):
     #         export_file.iloc[:, col_idx] = export_file.iloc[:, col_idx].map(id_dict)
             
@@ -290,9 +302,9 @@ with tab3:
         if st.button("Reset Optimals", key='reset3'):
             for key in st.session_state.keys():
                 del st.session_state[key]
-            if site_var1 == 'Draftkings':
+            if site_var3 == 'Draftkings':
                 st.session_state.working_seed = dk_lineups.copy()
-            elif site_var1 == 'Fanduel':
+            elif site_var3 == 'Fanduel':
                 st.session_state.working_seed = fd_lineups.copy()
         if 'data_export_display' in st.session_state:
             st.dataframe(st.session_state.data_export_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=500, use_container_width = True)
@@ -306,7 +318,7 @@ with tab3:
     with st.container():
         if 'working_seed' in st.session_state:
             # Create a new dataframe with summary statistics
-            if site_var1 == 'Draftkings':
+            if site_var3 == 'Draftkings':
                 summary_df = pd.DataFrame({
                     'Metric': ['Min', 'Average', 'Max', 'STDdev'],
                     'Salary': [
@@ -328,7 +340,7 @@ with tab3:
                         np.std(st.session_state.working_seed[:,8])
                     ]
                 })
-            elif site_var1 == 'Fanduel':
+            elif site_var3 == 'Fanduel':
                 summary_df = pd.DataFrame({
                     'Metric': ['Min', 'Average', 'Max', 'STDdev'],
                     'Salary': [
@@ -366,9 +378,9 @@ with tab3:
         tab1, tab2 = st.tabs(["Display Frequency", "Seed Frame Frequency"])
         with tab1:
             if 'data_export_display' in st.session_state:
-                if site_var1 == 'Draftkings':
+                if site_var3 == 'Draftkings':
                     player_columns = st.session_state.data_export_display.iloc[:, :6]
-                elif site_var1 == 'Fanduel':
+                elif site_var3 == 'Fanduel':
                     player_columns = st.session_state.data_export_display.iloc[:, :6]
                 
                 # Flatten the DataFrame and count unique values
@@ -402,9 +414,9 @@ with tab3:
                 )
         with tab2:
             if 'working_seed' in st.session_state:
-                if site_var1 == 'Draftkings':
+                if site_var3 == 'Draftkings':
                     player_columns = st.session_state.working_seed[:, :6]
-                elif site_var1 == 'Fanduel':
+                elif site_var3 == 'Fanduel':
                     player_columns = st.session_state.working_seed[:, :6]
                 
                 # Flatten the DataFrame and count unique values