added UI updates and second tab

src/streamlit_app.py

@@ -17,8 +17,45 @@ percentages_format = {'Pts% Boost': '{:.2%}', 'Reb% Boost': '{:.2%}', 'Ast% Boos
                       'Stl Boost%': '{:.2%}', 'Blk Boost%': '{:.2%}', 'TOV Boost%': '{:.2%}', 'FPPM Boost': '{:.2%}',
                       'Team FPPM Boost': '{:.2%}'}
 
+st.markdown("""
+<style>
+    /* Tab styling */
+    .stElementContainer [data-baseweb="button-group"] {
+        gap: 2.000rem;
+        padding: 4px;
+    }
+    .stElementContainer [kind="segmented_control"] {
+        height: 2.000rem;
+        white-space: pre-wrap;
+        background-color: #DAA520;
+        color: white;
+        border-radius: 20px;
+        gap: 1px;
+        padding: 10px 20px;
+        font-weight: bold;
+        transition: all 0.3s ease;
+    }
+    .stElementContainer [kind="segmented_controlActive"] {
+        height: 3.000rem;
+        background-color: #DAA520;
+        border: 3px solid #FFD700;
+        border-radius: 10px;
+        color: black;
+    }
+    .stElementContainer [kind="segmented_control"]:hover {
+        background-color: #FFD700;
+        cursor: pointer;
+    }
+
+    div[data-baseweb="select"] > div {
+        background-color: #DAA520;
+        color: white;
+    }
+
+</style>""", unsafe_allow_html=True)
+
 @st.cache_resource(ttl = 600)
-def init_baselines():
+def init_DEM():
     
     json_matchups = requests.get(NBA_DATA + '?sheet=DEM%20Matchups').json()
     raw_display = pd.DataFrame(json_matchups)
@@ -26,8 +63,10 @@ def init_baselines():
     matchups = raw_display[raw_display['Var'] != ""]
     matchups_dict = dict(zip(matchups['Team'], matchups['Opp']))
     
-    json_pg_dem = requests.get(NBA_DATA + '?sheet=PG_DEM_Calc').json()
-    raw_display = pd.DataFrame(json_pg_dem)
+    master_dem_json = requests.get(NBA_DATA + '?sheet=Master_DEM_Calc').json()
+    master_dem_frame = pd.DataFrame(master_dem_json)
+
+    raw_display = master_dem_frame[master_dem_frame['Position'] == 'PG']
     raw_display = raw_display.reset_index(drop=True)
     cols_to_check = ['Pts% Boost', 'Reb% Boost', 'Ast% Boost', '3p% Boost', 'Stl Boost%', 'Blk Boost%', 'TOV Boost%', 'FPPM Boost']
     raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
@@ -35,8 +74,7 @@ def init_baselines():
     raw_display['position'] = 'Point Guard'
     pg_dem = raw_display[raw_display['Acro'] != ""]
 
-    json_sg_dem = requests.get(NBA_DATA + '?sheet=SG_DEM_Calc').json()
-    raw_display = pd.DataFrame(json_sg_dem)
+    raw_display = master_dem_frame[master_dem_frame['Position'] == 'SG']
     raw_display = raw_display.reset_index(drop=True)
     cols_to_check = ['Pts% Boost', 'Reb% Boost', 'Ast% Boost', '3p% Boost', 'Stl Boost%', 'Blk Boost%', 'TOV Boost%', 'FPPM Boost']
     raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
@@ -44,8 +82,7 @@ def init_baselines():
     raw_display['position'] = 'Shooting Guard'
     sg_dem = raw_display[raw_display['Acro'] != ""]
     
-    json_sf_dem = requests.get(NBA_DATA + '?sheet=SF_DEM_Calc').json()
-    raw_display = pd.DataFrame(json_sf_dem)
+    raw_display = master_dem_frame[master_dem_frame['Position'] == 'SF']
     raw_display = raw_display.reset_index(drop=True)
     cols_to_check = ['Pts% Boost', 'Reb% Boost', 'Ast% Boost', '3p% Boost', 'Stl Boost%', 'Blk Boost%', 'TOV Boost%', 'FPPM Boost']
     raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
@@ -53,8 +90,7 @@ def init_baselines():
     raw_display['position'] = 'Small Forward'
     sf_dem = raw_display[raw_display['Acro'] != ""]
     
-    json_pf_dem = requests.get(NBA_DATA + '?sheet=PF_DEM_Calc').json()
-    raw_display = pd.DataFrame(json_pf_dem)
+    raw_display = master_dem_frame[master_dem_frame['Position'] == 'PF']
     raw_display = raw_display.reset_index(drop=True)
     cols_to_check = ['Pts% Boost', 'Reb% Boost', 'Ast% Boost', '3p% Boost', 'Stl Boost%', 'Blk Boost%', 'TOV Boost%', 'FPPM Boost']
     raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
@@ -62,8 +98,7 @@ def init_baselines():
     raw_display['position'] = 'Power Forward'
     pf_dem = raw_display[raw_display['Acro'] != ""]
     
-    json_c_dem = requests.get(NBA_DATA + '?sheet=C_DEM_Calc').json()
-    raw_display = pd.DataFrame(json_c_dem)
+    raw_display = master_dem_frame[master_dem_frame['Position'] == 'C']
     raw_display = raw_display.reset_index(drop=True)
     cols_to_check = ['Pts% Boost', 'Reb% Boost', 'Ast% Boost', '3p% Boost', 'Stl Boost%', 'Blk Boost%', 'TOV Boost%', 'FPPM Boost']
     raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
@@ -85,60 +120,119 @@ def init_baselines():
 
     return export_dem, matchups, matchups_dict
 
+@st.cache_resource(ttl = 600)
+def init_macro_tables():
+    team_macro_json = requests.get(NBA_DATA + '?sheet=Team_Macro').json()
+    team_macro_frame = pd.DataFrame(team_macro_json)
+    team_macro_frame = team_macro_frame.reset_index(drop=True)
+
+    team_off_frame = team_macro_frame[team_macro_frame['Data'] == 'Off']
+    team_off_frame = team_off_frame.reset_index(drop=True)
+
+    team_def_frame = team_macro_frame[team_macro_frame['Data'] == 'Def']
+    team_def_frame = team_def_frame.reset_index(drop=True)
+
+    team_combo_json = requests.get(NBA_DATA + '?sheet=Team%20Combo%20Data').json()
+    team_combo_frame = pd.DataFrame(team_combo_json)
+    team_combo_frame = team_combo_frame.reset_index(drop=True)
+
+    team_matchup_json = requests.get(NBA_DATA + '?sheet=Team%20Matchups').json()
+    team_matchup_frame = pd.DataFrame(team_matchup_json)
+    team_matchup_frame = team_matchup_frame.reset_index(drop=True)
+
+    return team_off_frame, team_def_frame, team_combo_frame, team_matchup_frame
+
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-overall_dem, matchups, matchups_dict = init_baselines()
-
-col1, col2 = st.columns([1, 9])
-with col1:
-    if st.button("Reset Data", key='reset1'):
-              st.cache_data.clear()
-              overall_dem, matchups, matchups_dict = init_baselines()
-    split_var1 = st.radio("View all teams or just this main slate's matchups?", ('Slate Matchups', 'All'), key='split_var1')
-    if split_var1 == 'Slate Matchups':
-        view_var1 = matchups.Opp.values.tolist()
-        split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
-        if split_var2 == 'Specific Teams':
-            team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = view_var1, key='team_var1')
-        elif split_var2 == 'All':
-            team_var1 = view_var1
-        split_var3 = st.radio("Would you like to view all positions or specific ones?", ('All', 'Specific Positions'), key='split_var3')
-        if split_var3 == 'Specific Positions':
-            pos_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['position'].unique(), key='pos_var1')
-        elif split_var3 == 'All':
-            pos_var1 = overall_dem.position.values.tolist()
-    if split_var1 == 'All':
-        split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
-        if split_var2 == 'Specific Teams':
-            team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['Acro'].unique(), key='team_var1')
-        elif split_var2 == 'All':
-            team_var1 = overall_dem.Acro.values.tolist()
-        split_var3 = st.radio("Would you like to view all positions or specific ones?", ('All', 'Specific Positions'), key='split_var3')
-        if split_var3 == 'Specific Positions':
-            pos_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['position'].unique(), key='pos_var1')
-        elif split_var3 == 'All':
-            pos_var1 = overall_dem.position.values.tolist()
-with col2:
-    if split_var1 == 'Slate Matchups':
-        dem_display = overall_dem[overall_dem['Acro'].isin(view_var1)]
-        dem_display['Team (Getting Boost)'] = dem_display['Acro'].map(matchups_dict)
-        dem_display.rename(columns={"Acro": "Opp (Giving Boost)"}, inplace = True)
-        dem_display = dem_display[['Team (Getting Boost)', 'Opp (Giving Boost)', 'G', 'Pts% Boost', 'Reb% Boost', 'Ast% Boost', '3p% Boost',
-                                   'Stl Boost%', 'Blk Boost%', 'TOV Boost%', 'FPPM', 'FPPM Boost', 'Team FPPM Boost', 'position']]
-        dem_display = dem_display[dem_display['Team (Getting Boost)'].isin(team_var1)]
-        dem_display = dem_display[dem_display['position'].isin(pos_var1)]
-        dem_display = dem_display.sort_values(by='FPPM Boost', ascending=False)
-    elif split_var1 == 'All':
-        dem_display = overall_dem[overall_dem['Acro'].isin(team_var1)]
-        dem_display = dem_display[dem_display['position'].isin(pos_var1)]
-        dem_display = dem_display.sort_values(by='FPPM Boost', ascending=False)
-        dem_display.rename(columns={"Team": "Team (Giving Boost)"}, inplace = True)
-        dem_display = dem_display.set_index('Team (Giving Boost)')
-    st.dataframe(dem_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
-    st.download_button(
-        label="Export DEM Numbers",
-        data=convert_df_to_csv(overall_dem),
-        file_name='DEM_export.csv',
-        mime='text/csv',
-    )
+selected_tab = st.segmented_control(
+    "Select Tab",
+    options=["DEM Matchups", "Team Macro Tables"],
+    selection_mode='single',
+    default='DEM Matchups',
+    width='stretch',
+    label_visibility='collapsed',
+    key='tab_selector'
+)
+
+if selected_tab == 'DEM Matchups':
+
+    overall_dem, matchups, matchups_dict = init_DEM()
+
+    col1, col2 = st.columns([1, 9])
+    with col1:
+        if st.button("Reset Data", key='reset1'):
+                st.cache_data.clear()
+                overall_dem, matchups, matchups_dict = init_DEM()
+        split_var1 = st.radio("View all teams or just this main slate's matchups?", ('Slate Matchups', 'All'), key='split_var1')
+        if split_var1 == 'Slate Matchups':
+            view_var1 = matchups.Opp.values.tolist()
+            split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
+            if split_var2 == 'Specific Teams':
+                team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = view_var1, key='team_var1')
+            elif split_var2 == 'All':
+                team_var1 = view_var1
+            split_var3 = st.radio("Would you like to view all positions or specific ones?", ('All', 'Specific Positions'), key='split_var3')
+            if split_var3 == 'Specific Positions':
+                pos_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['position'].unique(), key='pos_var1')
+            elif split_var3 == 'All':
+                pos_var1 = overall_dem.position.values.tolist()
+        if split_var1 == 'All':
+            split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
+            if split_var2 == 'Specific Teams':
+                team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['Acro'].unique(), key='team_var1')
+            elif split_var2 == 'All':
+                team_var1 = overall_dem.Acro.values.tolist()
+            split_var3 = st.radio("Would you like to view all positions or specific ones?", ('All', 'Specific Positions'), key='split_var3')
+            if split_var3 == 'Specific Positions':
+                pos_var1 = st.multiselect('Which teams would you like to include in the tables?', options = overall_dem['position'].unique(), key='pos_var1')
+            elif split_var3 == 'All':
+                pos_var1 = overall_dem.position.values.tolist()
+    with col2:
+        if split_var1 == 'Slate Matchups':
+            dem_display = overall_dem[overall_dem['Acro'].isin(view_var1)]
+            dem_display['Team (Getting Boost)'] = dem_display['Acro'].map(matchups_dict)
+            dem_display.rename(columns={"Acro": "Opp (Giving Boost)"}, inplace = True)
+            dem_display = dem_display[['Team (Getting Boost)', 'Opp (Giving Boost)', 'G', 'Pts% Boost', 'Reb% Boost', 'Ast% Boost', '3p% Boost',
+                                    'Stl Boost%', 'Blk Boost%', 'TOV Boost%', 'FPPM', 'FPPM Boost', 'Team FPPM Boost', 'position']]
+            dem_display = dem_display[dem_display['Team (Getting Boost)'].isin(team_var1)]
+            dem_display = dem_display[dem_display['position'].isin(pos_var1)]
+            dem_display = dem_display.sort_values(by='FPPM Boost', ascending=False)
+        elif split_var1 == 'All':
+            dem_display = overall_dem[overall_dem['Acro'].isin(team_var1)]
+            dem_display = dem_display[dem_display['position'].isin(pos_var1)]
+            dem_display = dem_display.sort_values(by='FPPM Boost', ascending=False)
+            dem_display.rename(columns={"Team": "Team (Giving Boost)"}, inplace = True)
+            dem_display = dem_display.set_index('Team (Giving Boost)')
+        st.dataframe(dem_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
+        st.download_button(
+            label="Export DEM Numbers",
+            data=convert_df_to_csv(overall_dem),
+            file_name='DEM_export.csv',
+            mime='text/csv',
+        )
+
+if selected_tab == 'Team Macro Tables':
+    team_off_frame, team_def_frame, team_combo_frame, team_matchup_frame = init_macro_tables()
+    col1, col2 = st.columns([1, 9])
+    with col1:
+        if st.button("Reset Data", key='reset2'):
+                st.cache_data.clear()
+                team_off_frame, team_def_frame, team_combo_frame, team_matchup_frame = init_macro_tables()
+        table_var2 = st.selectbox("Select Table", options=['Team Offense', 'Team Defense', 'Team Combo', 'Team Matchups'], key='table_var2')
+    with col2:
+        if table_var2 == 'Team Offense':
+            team_macro_display = team_off_frame
+        elif table_var2 == 'Team Defense':
+            team_macro_display = team_def_frame
+        elif table_var2 == 'Team Combo':
+            team_macro_display = team_combo_frame
+        elif table_var2 == 'Team Matchups':
+            team_macro_display = team_matchup_frame
+        st.dataframe(team_macro_display.set_index('Team').style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+        st.download_button(
+            label="Export Table Data",
+            data=convert_df_to_csv(team_macro_display),
+            file_name='Team_Macro_export.csv',
+            mime='text/csv',
+        )