Python 3.x 向DatetimeIndex添加分钟数

Python 3.x 向DatetimeIndex添加分钟数,python-3.x,pandas,Python 3.x,Pandas,我有一个包含日期的索引 DatetimeIndex(['2004-01-02', '2004-01-05', '2004-01-06', '2004-01-07', '2004-01-08', '2004-01-09', '2004-01-12', '2004-01-13', '2004-01-14', '2004-01-15', ... '2015-12-17', '2015-12-18', '2015-1

我有一个包含日期的索引

DatetimeIndex(['2004-01-02', '2004-01-05', '2004-01-06', '2004-01-07',
           '2004-01-08', '2004-01-09', '2004-01-12', '2004-01-13',
           '2004-01-14', '2004-01-15',
           ...
           '2015-12-17', '2015-12-18', '2015-12-21', '2015-12-22',
           '2015-12-23', '2015-12-24', '2015-12-28', '2015-12-29',
           '2015-12-30', '2015-12-31'],
          dtype='datetime64[ns]', length=3021, freq=None)
现在,我要为每一天生成每一分钟(24*60=1440分钟),并用所有天和分钟制作一个索引

结果应该如下所示:

['2004-01-02 00:00:00', '2004-01-02 00:01:00', ..., '2004-01-02 23:59:00',
 '2004-01-03 00:00:00', '2004-01-03 00:01:00', ..., '2004-01-03 23:59:00',
 ...
 '2015-12-31 00:00:00', '2015-12-31 00:01:00', ..., '2015-12-31 23:59:00']

有什么聪明的方法吗?

您应该能够在这里使用
.asfreq()

>>> import pandas as pd 
>>> days = pd.date_range(start='2018-01-01', days=10)
>>> df = pd.DataFrame(list(range(len(days))), index=days)
>>> df.asfreq('min')                                                                                                                                     
                       0
2018-01-01 00:00:00  0.0
2018-01-01 00:01:00  NaN
2018-01-01 00:02:00  NaN
2018-01-01 00:03:00  NaN
2018-01-01 00:04:00  NaN
2018-01-01 00:05:00  NaN
2018-01-01 00:06:00  NaN
# ...

>>> df.shape                                                                                                                                             
(10, 1)

>>> df.asfreq('min').shape                                                                                                                               
(12961, 1)

如果出于某种原因,这不起作用,你可能还想研究一下;然后,在连接的结果上执行pd.to_datetime()。

最终的
datetime索引应该是什么样子的
?一些日期在3天内不同
'2004-01-02',2004-01-05'
。这是故意的吗?@RomanPerekhrest是的。假期取消。我只是想为这几天做些准备。否则,使用range会很容易。我想我可以使用join。它是独立索引还是数据帧的索引?