Refactor general exposures dataframe creation in create_general_exposures function

- Updated the creation of the general exposures dataframe to use a more concise dictionary format, improving code readability.
- Changed the output method from st.table to st.write for better integration with Streamlit's display capabilities, enhancing user experience.

global_func/create_general_exposures.py

@@ -25,10 +25,10 @@ def create_general_exposures(df: pd.DataFrame, entrants: list = None):
         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 = pd.DataFrame()
-            general_frame['Stat'] = each_col
-            general_frame['Average'] = each_general / each_general_len_set[general_count_var]
-            general_frame = general_frame[['Stat', 'Average']]
+            general_frame = pd.DataFrame({
+                'Stat': [each_col],
+                '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:
@@ -36,6 +36,6 @@ def create_general_exposures(df: pd.DataFrame, entrants: list = None):
             else:
                 general_exposures = pd.merge(general_exposures, general_frame, on='Stat', how='outer')
             general_count_var += 1
-            st.table(general_exposures)
+            st.write(general_exposures)
 
     return general_exposures