eland.groupby.DataFrameGroupBy.min#

DataFrameGroupBy.min(numeric_only: bool = True) pd.DataFrame#

计算每个组的最小值。

参数#

numeric_only: {True, False, None} 默认值为 True

要返回的哪种数据类型 - True: 将所有值返回为 float64,删除 NaN/NaT 值 - None: 尽可能将所有值返回为相同的 dtype,删除 NaN/NaT - False: 尽可能将所有值返回为相同的 dtype,保留 NaN/NaT

返回值#

pandas.DataFrame

每个组的每个数值列的最小值

另请参阅#

pandas.core.groupby.GroupBy.min

示例#

>>> df = ed.DataFrame(
...   "http://localhost:9200", "flights",
...   columns=["AvgTicketPrice", "Cancelled", "dayOfWeek", "timestamp", "DestCountry"]
... )
>>> df.groupby("DestCountry").min(numeric_only=False) 
             AvgTicketPrice  Cancelled  dayOfWeek           timestamp
DestCountry
AE               110.799911      False          0 2018-01-01 19:31:30
AR               125.589394      False          0 2018-01-01 01:30:47
AT               100.020531      False          0 2018-01-01 05:24:19
AU               102.294312      False          0 2018-01-01 00:00:00
CA               100.557251      False          0 2018-01-01 00:44:08
...                     ...        ...        ...                 ...
RU               101.004005      False          0 2018-01-01 01:01:51
SE               102.877190      False          0 2018-01-01 04:09:38
TR               142.876465      False          0 2018-01-01 06:45:17
US               100.145966      False          0 2018-01-01 00:06:27
ZA               102.002663      False          0 2018-01-01 06:44:44

[32 rows x 4 columns]