Refactor tab1 layout and improve user interface for ROO projection view

app.py

@@ -281,84 +281,105 @@ with st.sidebar:
         st.write(f'Total LevX: {levx_sum:.2f}')
 
 with tab1:
+    with st.container():
+        st.info("Advanced view includes all stats and thresholds, simple includes just basic columns for ease of use on mobile")
+    with st.container():
+        # First row - timestamp and reset button
+        col1, col2 = st.columns([3, 1])
+        with col1:
+            st.info(t_stamp)
+        with col2:
+            if st.button("Load/Reset Data", key='reset1'):
+                st.cache_data.clear()
+                dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp, roo_backlog = load_overall_stats()
+                id_dict = dict(zip(roo_raw.Player, roo_raw.player_ID))
+                dk_lineups = init_DK_lineups()
+                fd_lineups = init_FD_lineups()
+                t_stamp = f"Last Update: " + str(timestamp) + f" CST"
+                for key in st.session_state.keys():
+                    del st.session_state[key]
 
-    col1, col2 = st.columns([1, 9])
+        # Second row - main options
+        col1, col2, col3 = st.columns(3)
+        with col1:
+            view_var2 = st.radio("View Type", ('Simple', 'Advanced'), key='view_var2')
+        with col2:
+            site_var2 = st.radio("Site", ('Draftkings', 'Fanduel'), key='site_var2')
+        with col3:
+            slate_split = st.radio("Slate Type", ('Main Slate', 'Secondary', 'Backlog'), key='slate_split')
 
-    with col1:
-        st.info(t_stamp)
-        if st.button("Load/Reset Data", key='reset1'):
-            st.cache_data.clear()
-            dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp, roo_backlog = load_overall_stats()
-            id_dict = dict(zip(roo_raw.Player, roo_raw.player_ID))
-            dk_lineups = init_DK_lineups()
-            fd_lineups = init_FD_lineups()
-            t_stamp = f"Last Update: " + str(timestamp) + f" CST"
-            for key in st.session_state.keys():
-                del st.session_state[key]
-        view_var2 = st.radio("What view would you like to display?", ('Simple', 'Advanced'), key='view_var2')
-        st.info("Advanced view includes all stats and thresholds, simple includes just basic columns for ease of use on mobile")
-        site_var2 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var2')
+        # Process site selection
         if site_var2 == 'Draftkings':
             site_baselines = roo_raw[roo_raw['site'] == 'Draftkings']
             site_backlog = roo_backlog[roo_backlog['site'] == 'Draftkings']
         elif site_var2 == 'Fanduel':
             site_baselines = roo_raw[roo_raw['site'] == 'Fanduel']
             site_backlog = roo_backlog[roo_backlog['site'] == 'Fanduel']
-        slate_split = st.radio("Are you viewing the main slate or the secondary slate?", ('Main Slate', 'Secondary', 'Backlog'), key='slate_split')
+
+        # Process slate selection
         if slate_split == 'Main Slate':
             raw_baselines = site_baselines[site_baselines['slate'] == 'Main Slate']
         elif slate_split == 'Secondary':
             raw_baselines = site_baselines[site_baselines['slate'] == 'Secondary Slate']
         elif slate_split == 'Backlog':
             raw_baselines = site_backlog
-            view_all = st.checkbox("Do you want to view all dates?", key='view_all')
+            # Third row - backlog options
+            col1, col2 = st.columns(2)
+            with col1:
+                view_all = st.checkbox("View all dates?", key='view_all')
+            with col2:
+                if not view_all:
+                    date_var2 = st.date_input("Select date", key='date_var2')
+            
             if view_all:
-                raw_baselines = raw_baselines
                 raw_baselines = raw_baselines.sort_values(by=['Median', 'Date'], ascending=[False, False])
             else:
-                date_var2 = st.date_input("Which date would you like to view?", key='date_var2')
                 raw_baselines = raw_baselines[raw_baselines['Date'] == date_var2.strftime('%m-%d-%Y')]
                 raw_baselines = raw_baselines.sort_values(by='Median', ascending=False)
-        split_var2 = st.radio("Are you running the full slate or certain games?", ('Full Slate Run', 'Specific Games'), key='split_var2')
-        if split_var2 == 'Specific Games':
-            team_var2 = st.multiselect('Which teams would you like to include in the ROO?', options = raw_baselines['Team'].unique(), key='team_var2')
-        elif split_var2 == 'Full Slate Run':
-            team_var2 = raw_baselines.Team.values.tolist()
-        pos_var2 = st.selectbox('View specific position?', options = ['All', 'PG', 'SG', 'SF', 'PF', 'C'], key='pos_var2')
 
-    with col2:
-        display_container_1 = st.empty()
-        display_dl_container_1 = st.empty()
-        display_proj = raw_baselines[raw_baselines['Team'].isin(team_var2)]
-        if view_var2 == 'Advanced':
-            display_proj = display_proj[['Player', 'Minutes Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
-                                        'Own', 'Small_Own', 'Large_Own', 'Cash_Own', 'CPT_Own', 'LevX', 'ValX']]
-        elif view_var2 == 'Simple':
-            display_proj = display_proj[['Player', 'Team', 'Position', 'Median', 'GPP%', 'Own']]
-        export_data = display_proj.copy()
-
-
-        display_proj = display_proj.set_index('Player')
-        st.session_state.display_proj = display_proj
-            
-        with display_container_1:
-            display_container = st.empty()
-            if 'display_proj' in st.session_state:
-                if pos_var2 == 'All':
-                    st.session_state.display_proj = st.session_state.display_proj
-                elif pos_var2 != 'All':
-                    st.session_state.display_proj = st.session_state.display_proj[st.session_state.display_proj['Position'].str.contains(pos_var2)]
-                st.dataframe(st.session_state.display_proj.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(roo_format, precision=2), height=1000, use_container_width = True)
+        # Fourth row - final options
+        col1, col2 = st.columns(2)
+        with col1:
+            split_var2 = st.radio("Slate Range", ('Full Slate Run', 'Specific Games'), key='split_var2')
+            if split_var2 == 'Specific Games':
+                team_var2 = st.multiselect('Select teams for ROO', options=raw_baselines['Team'].unique(), key='team_var2')
+            else:
+                team_var2 = raw_baselines.Team.values.tolist()
+        with col2:
+            pos_var2 = st.selectbox('Position Filter', options=['All', 'PG', 'SG', 'SF', 'PF', 'C'], key='pos_var2')
+    
+    display_container_1 = st.empty()
+    display_dl_container_1 = st.empty()
+    display_proj = raw_baselines[raw_baselines['Team'].isin(team_var2)]
+    if view_var2 == 'Advanced':
+        display_proj = display_proj[['Player', 'Minutes Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
+                                    'Own', 'Small_Own', 'Large_Own', 'Cash_Own', 'CPT_Own', 'LevX', 'ValX']]
+    elif view_var2 == 'Simple':
+        display_proj = display_proj[['Player', 'Team', 'Position', 'Median', 'GPP%', 'Own']]
+    export_data = display_proj.copy()
+
+
+    display_proj = display_proj.set_index('Player')
+    st.session_state.display_proj = display_proj
         
-        with display_dl_container_1:
-                display_dl_container = st.empty()
-                if 'display_proj' in st.session_state:
-                    st.download_button(
-                                label="Export Tables",
-                                data=convert_df_to_csv(export_data),
-                                file_name='NBA_ROO_export.csv',
-                                mime='text/csv',
-                    )
+    with display_container_1:
+        display_container = st.empty()
+        if 'display_proj' in st.session_state:
+            if pos_var2 == 'All':
+                st.session_state.display_proj = st.session_state.display_proj
+            elif pos_var2 != 'All':
+                st.session_state.display_proj = st.session_state.display_proj[st.session_state.display_proj['Position'].str.contains(pos_var2)]
+            st.dataframe(st.session_state.display_proj.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(roo_format, precision=2), height=1000, use_container_width = True)
+    
+    with display_dl_container_1:
+            display_dl_container = st.empty()
+            if 'display_proj' in st.session_state:
+                st.download_button(
+                            label="Export Tables",
+                            data=convert_df_to_csv(export_data),
+                            file_name='NBA_ROO_export.csv',
+                            mime='text/csv',
+                )
 
 with tab2:
     col1, col2 = st.columns([1, 7])