Untitled

# ...

for _, row in filtered_df.iterrows():
    eprm_table_name = row['eprm_table_name']
    eprm_join_cols_entity = row['eprm_join_cols_entity']
    eprm_join_cols_reim = row['eprm_join_cols_reim']
    eprm_table_alias = row['eprm_table_alias']

    # Split the strings by ',' to get individual column assignments
    columns_entity = eprm_join_cols_entity.split(',') if eprm_join_cols_entity else []
    columns_reim = eprm_join_cols_reim.split(',') if eprm_join_cols_reim else []

    # Compare the lengths of the column assignments
    entity_length = len(columns_entity)
    reim_length = len(columns_reim)
    max_length = max(entity_length, reim_length)

    # Pad the shorter list with empty elements to match the length of the longer list
    columns_entity += [''] * (max_length - entity_length)
    columns_reim += [''] * (max_length - reim_length)

    # Construct the modified assignment string
    assignment_string = ''
    for col_entity, col_reim in zip(columns_entity, columns_reim):
        # Extract the column name after '='
        col_name_entity = col_entity.split('=')[0].strip()
        col_name_reim = col_reim.split('=')[0].strip()
        # Append the modified assignment to the string
        assignment_string += f"{col_reim.replace(col_name_reim, eprm_table_alias + '.' + col_name_entity)}, "

    # Remove the trailing comma and whitespace
    assignment_string = assignment_string.rstrip(', ')
    assignment_string = assignment_string.replace("AND", ",")
    eprm_join_reim = assignment_string

    # ...