def METHOD_NAME():
    """prepare sample data, use train_schema, not the origin schema"""
    data_path = 'data/'
    sample_cnt = 10000  # you can prepare sample data by yourself
    print(
        f'Prepare train data, use {sample_cnt} rows, save it as train_sample.csv')
    df = pd.read_csv(data_path + 'train.csv',
                     usecols=[c[0] for c in train_schema])
    # take a portion from train sample data
    df_tmp = df.sample(n=sample_cnt)
    assert len(df_tmp) == sample_cnt
    attr_count = df_tmp.is_attributed.value_counts()
    print(attr_count)
    # 'is_attributed' must have two values: 0, 1
    assert attr_count.count() > 1
    df_tmp.to_csv('train_sample.csv', index=False)
    del df_tmp
    del df
    gc.collect()