Update app.py

app.py

@@ -26,6 +26,7 @@ gc = gspread.service_account_from_dict(credentials)
 st.set_page_config(layout="wide")
 
 american_format = {'ML': '{:.2%}'}
+mma_format = {'ML_perc': '{:.2%}', 'Min_%': '{:.2%}', 'Med_%': '{:.2%}', }
 
 @st.cache_resource(ttl = 600)
 def init_baselines():
@@ -35,20 +36,42 @@ def init_baselines():
     tennis_model = frame_hold.drop_duplicates(subset='Player')
     tennis_model = tennis_model.set_index('Player')
     tennis_model = tennis_model.sort_values(by='Median', ascending=False)
+    
+    sh = gc.open_by_url("https://docs.google.com/spreadsheets/d/1T4n3-KC141n2XwhRCqLssuk1nVdHjsBPSdb8Q6LopuY/edit?gid=0#gid=0")
+    worksheet = sh.worksheet('JBOTTUM_MMA')
+    frame_hold = pd.DataFrame(worksheet.get_all_records())
+    mma_model = frame_hold.drop_duplicates(subset='Player')
+    mma_model = mma_model.set_index('Player')
+    mma_model = mma_model.sort_values(by='Median', ascending=False)
+    mma_model = mma_model[['Player', 'Opponent', 'Salary', 'Floor_Adj', 'Median', 'Ceiling_Adj', 'ML_perc', 'Min_Win', 'Min_%', 'Median_Win', 'Med_%', 'Max_Win']]
+    
 
-    return tennis_model
+    return tennis_model, mma_model
 
 @st.cache_resource()
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-tennis_base = init_baselines()
+tennis_base, mma_base = init_baselines()
+
+tab1, tab2 = st.tabs(['Tennis Models', 'MMA Models'])
+
+with tab1:
+    with st.container():
+              st.dataframe(tennis_base.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(american_format, precision=2), height = 1000, use_container_width = True)
+              st.download_button(
+                      label="Export Tables",
+                      data=convert_df_to_csv(tennis_base),
+                      file_name='tennis_model_export.csv',
+                      mime='text/csv',
+              )
 
-with st.container():
-          st.dataframe(tennis_base.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(american_format, precision=2), height = 1000, use_container_width = True)
-          st.download_button(
-                  label="Export Tables",
-                  data=convert_df_to_csv(tennis_base),
-                  file_name='tennis_model_export.csv',
-                  mime='text/csv',
-          )
+with tab2:
+    with st.container():
+              st.dataframe(mma_base.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(mma_format, precision=2), height = 1000, use_container_width = True)
+              st.download_button(
+                      label="Export Tables",
+                      data=convert_df_to_csv(mma_base),
+                      file_name='mma_model_export.csv',
+                      mime='text/csv',
+              )