# creates an empty list to append to
differences = []
# for all the IDs in the dataframe that should not change check if this record is the same in the database
# must use reset_index() so the equals() will work as I expect it to
# if it is not the same, append to a list which has the Aspn ID that is failing, along with the columns that changed
for unique_id in new_df['ID'].tolist():
    if new_df.loc[new_df['ID'] == unique_id].reset_index(drop=True).equals(sql_df.loc[sql_df['ID'] == unique_id].reset_index(drop=True)) is False:
        bad_columns = []
        for column in new_df.columns.tolist():
            if new_df.loc[new_df['ID'] == unique_id][column].reset_index(drop=True).equals(sql_df.loc[sql_df['ID'] == unique_id][column].reset_index(drop=True)) is False:
                bad_columns.append(column)
        differences.append([unique_id, bad_columns])