Enhance background gradient application in app.py

- Updated the background gradient method in the dataframe display to specify the axis parameter, improving visual clarity in the presentation of general exposures.
- Ensured consistent styling across different entry selections while maintaining existing functionality.

app.py

@@ -293,13 +293,13 @@ with tab2:
                 if entry_parse_var == 'All':
                     st.session_state['general_frame'] = create_general_exposures(working_df)
                     st.dataframe(st.session_state['general_frame'].
-                        style.background_gradient(cmap='RdYlGn').
+                        style.background_gradient(cmap='RdYlGn', axis=1).
                         format(formatter='{:.2%}', subset=st.session_state['general_frame'].iloc[:, 1:].select_dtypes(include=['number']).columns),
                         hide_index=True)
                 else:
                     st.session_state['general_frame'] = create_general_exposures(working_df, entry_names)
                     st.dataframe(st.session_state['general_frame'].
-                        style.background_gradient(cmap='RdYlGn').
+                        style.background_gradient(cmap='RdYlGn', axis=1).
                         format(formatter='{:.2%}', subset=st.session_state['general_frame'].iloc[:, 1:].select_dtypes(include=['number']).columns),
                         hide_index=True)
 

global_func/create_general_exposures.py

@@ -1,5 +1,4 @@
 import pandas as pd
-import streamlit as st
 
 def create_general_exposures(df: pd.DataFrame, entrants: list = None):
     check_cols = ['salary', 'actual_fpts', 'actual_own', 'dupes']
@@ -25,17 +24,14 @@ def create_general_exposures(df: pd.DataFrame, entrants: list = None):
         each_general_len_set = [general_contest_len, general_len_1per, general_len_5per, general_len_10per, general_len_20per]
         general_count_var = 0
         for each_general in each_general_set:
-            st.write(f'{each_col} Sum is {each_general}, Average is {each_general / each_general_len_set[general_count_var]}')
             general_frame['Stat'] = [each_col]
             general_frame['Average'] = [each_general / each_general_len_set[general_count_var]]
-            st.write(general_frame)
             general_frame = general_frame.rename(columns={'Average': f'Average {each_set_name[general_count_var]}'})
             if len(general_exposures) == 0:
                 general_row = general_frame
             else:
                 general_row = pd.merge(general_exposures, general_frame, on='Stat', how='outer')
             general_count_var += 1
-            st.write(general_exposures)
         if len(general_exposures) == 0:
             general_exposures = general_row
         else: