def METHOD_NAME(self, start_time_millis, end_time_millis) -> pd.DataFrame:
    steps = {}
    steps_data = self.retrieve_data(self.api, start_time_millis, end_time_millis, "derived:com.google.step_count.delta:com.google.android.gms:estimated_steps")
    for daily_step_data in steps_data['bucket']:
        local_date = datetime.fromtimestamp(int(daily_step_data['startTimeMillis']) / 1000,
                                        tz=pytz.timezone(str(get_localzone())))
        local_date_str = local_date.strftime(DATE_FORMAT)
        data_point = daily_step_data['dataset'][0]['point']
        if data_point:
            count = data_point[0]['value'][0]['intVal']
            data_source_id = data_point[0]['originDataSourceId']
            steps[local_date_str] = {'steps': count, 'originDataSourceId': data_source_id}
    ret = pd.DataFrame.from_dict(steps)
    ret = ret.T
    ret = ret.drop('originDataSourceId', axis=1)
    ret = ret.reset_index(drop=False)
    return ret