python-将DateTimeindex转换为仅包含年,时和日,而不包含时间信息

我有一个带有索引的数据框,该索引还包含Hour：second：…,但我只希望它包含年,月,日等日期.

索引是否仍可能是DateTimeIndex但仅包含年,月,日？

当前索引如下：

my_index = DatetimeIndex(['2017-08-25', '2017-08-24', '2017-08-23', '2017-08-22',
           '2017-08-21', '2017-08-20', '2017-08-19', '2017-08-18',
           '2017-08-17', '2017-08-16',
           ...
           '2015-07-19', '2015-07-18', '2015-07-17', '2015-07-16',
           '2015-07-15', '2015-07-14', '2015-07-13', '2015-07-12',
           '2015-07-11', '2015-07-10'],
          dtype='datetime64[ns]', length=778, freq=None)

我可以做：

only_date_index = [el.date() for el in my_index]

但是,如果我想在熊猫中使用重采样功能,则会收到错误消息：
TypeError：仅对DatetimeIndex,timedeltaIndex或Periodindex有效,但具有“ Index”的实例.

解决方法:

您需要DatetimeIndex.floor：

myIndex = df.index.floor('D')

样品：

rng = pd.date_range('2017-04-03 15:00:45', periods=10, freq='24T')
df = pd.DataFrame({'a': range(10)}, index=rng)  
print (df)
                     a
2017-04-03 15:00:45  0
2017-04-03 15:24:45  1
2017-04-03 15:48:45  2
2017-04-03 16:12:45  3
2017-04-03 16:36:45  4
2017-04-03 17:00:45  5
2017-04-03 17:24:45  6
2017-04-03 17:48:45  7
2017-04-03 18:12:45  8
2017-04-03 18:36:45  9

myIndex = df.index.floor('D')
print (myIndex)
DatetimeIndex(['2017-04-03', '2017-04-03', '2017-04-03', '2017-04-03',
               '2017-04-03', '2017-04-03', '2017-04-03', '2017-04-03',
               '2017-04-03', '2017-04-03'],
              dtype='datetime64[ns]', freq=None)

感谢您提供另一个解决方案Deckerz-使用DatetimeIndex.normalize：

myIndex = df.index.normalize()
print (myIndex)
DatetimeIndex(['2017-04-03', '2017-04-03', '2017-04-03', '2017-04-03',
               '2017-04-03', '2017-04-03', '2017-04-03', '2017-04-03',
               '2017-04-03', '2017-04-03'],
              dtype='datetime64[ns]', freq=None)

时序：

ix = pd.date_range('1970-01-01', '2200-01-15', freq='1H')

print (len(ix))
2016481

In [68]: %timeit (ix.normalize())
10 loops, best of 3: 178 ms per loop

In [69]: %timeit (ix.floor('d'))
10 loops, best of 3: 38.4 ms per loop

#solution from Dror (https://stackoverflow.com/questions/45954497/in-pandas-group-by-date-from-datetimeindex)
In [70]: %timeit pd.to_datetime(ix.date)
1 loop, best of 3: 5.09 s per loop