Update app.py

app.py

@@ -39,20 +39,14 @@ gcservice_account = init_conn()
 dk_player_url = 'https://docs.google.com/spreadsheets/d/1lMLxWdvCnOFBtG9dhM0zv2USuxZbkogI_2jnxFfQVVs/edit#gid=1828092624'
 CSV_URL = 'https://docs.google.com/spreadsheets/d/1lMLxWdvCnOFBtG9dhM0zv2USuxZbkogI_2jnxFfQVVs/edit#gid=1828092624'
 
+player_roo_format = {'Top_finish': '{:.2%}','Top_5_finish': '{:.2%}', 'Top_10_finish': '{:.2%}', '100+%': '{:.2%}', '10x%': '{:.2%}', '11x%': '{:.2%}',
+                   '12x%': '{:.2%}','LevX': '{:.2%}'}
+
 @st.cache_resource(ttl = 600)
 def init_baselines():
     sh = gcservice_account.open_by_url(dk_player_url)
     worksheet = sh.worksheet('ROO')
     raw_display = pd.DataFrame(worksheet.get_all_records())
-    #raw_display["Salary"] = raw_display["Salary"].replace(",", "", regex=True).astype(float)
-    #raw_display['Top_finish'] = raw_display['Top_finish'].str.replace('%', '').astype(float)/100
-    #raw_display['Top_5_finish'] = raw_display['Top_5_finish'].str.replace('%', '').astype(float)/100
-    #raw_display['Top_10_finish'] = raw_display['Top_10_finish'].str.replace('%', '').astype(float)/100
-    #raw_display['100+%'] = raw_display['100+%'].str.replace('%', '').astype(float)/100
-    #raw_display['10x%'] = raw_display['10x%'].str.replace('%', '').astype(float)/100
-    #raw_display['11x%'] = raw_display['11x%'].str.replace('%', '').astype(float)/100
-    #raw_display['12x%'] = raw_display['12x%'].str.replace('%', '').astype(float)/100
-    #raw_display['LevX'] = raw_display['LevX'].str.replace('%', '').astype(float)/100
     roo_data = raw_display
     
     worksheet = sh.worksheet('DK_CSV')
@@ -94,7 +88,7 @@ with tab1:
               salaryCut = 0
     hold_container = st.empty()
     display = hold_display.set_index('Player')
-    st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+    st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(player_roo_format, precision=2), use_container_width = True)
     st.download_button(
         label="Export Projections",
         data=convert_df_to_csv(display),