eland.DataFrame.mode#

DataFrame.mode(numeric_only: bool = False, dropna: bool = True, es_size: int = 10) → DataFrame#

计算 DataFrame 的众数

参数#

numeric_only: {True, False} 默认值为 False

要返回的哪种数据类型 - True: 返回所有数字或时间戳列 - False: 返回所有列

dropna: {True, False} 默认值为 True

  • True: 不考虑 NaN/NaT 的计数。

  • False: 考虑 NaN/NaT 的计数。

es_size: 默认值为 10

如果众数有多个值，要返回的行数

另请参见#

pandas.DataFrame.mode

示例#

>>> ed_ecommerce = ed.DataFrame('http://localhost:9200', 'ecommerce')
>>> ed_df = ed_ecommerce.filter(["total_quantity", "geoip.city_name", "customer_birth_date", "day_of_week", "taxful_total_price"])
>>> ed_df.mode(numeric_only=False)
   total_quantity geoip.city_name customer_birth_date day_of_week  taxful_total_price
0               2        New York                 NaT    Thursday               53.98

>>> ed_df.mode(numeric_only=True)
   total_quantity  taxful_total_price
0               2               53.98

>>> ed_df = ed_ecommerce.filter(["products.tax_amount","order_date"])
>>> ed_df.mode()
   products.tax_amount          order_date
0                  0.0 2016-12-02 20:36:58
1                  NaN 2016-12-04 23:44:10
2                  NaN 2016-12-08 06:21:36
3                  NaN 2016-12-08 09:38:53
4                  NaN 2016-12-12 11:38:24
5                  NaN 2016-12-12 19:46:34
6                  NaN 2016-12-14 18:00:00
7                  NaN 2016-12-15 11:38:24
8                  NaN 2016-12-22 19:39:22
9                  NaN 2016-12-24 06:21:36

>>> ed_df.mode(es_size = 3)
   products.tax_amount          order_date
0                  0.0 2016-12-02 20:36:58
1                  NaN 2016-12-04 23:44:10
2                  NaN 2016-12-08 06:21:36