Question

我正在尝试使用Pandas在预定义的一组日期中为每小时生成一组间隔。我用过：

import pandas as pd

print pd.date_range(start='2013-04-01', end='2013-04-30', freq='1H')

DatetimeIndex(['2013-04-01 00:00:00', '2013-04-01 01:00:00',
               '2013-04-01 02:00:00', '2013-04-01 03:00:00',
               '2013-04-01 04:00:00', '2013-04-01 05:00:00',
               '2013-04-01 06:00:00', '2013-04-01 07:00:00',
               '2013-04-01 08:00:00', '2013-04-01 09:00:00',
               ...
               '2013-04-29 15:00:00', '2013-04-29 16:00:00',
               '2013-04-29 17:00:00', '2013-04-29 18:00:00',
               '2013-04-29 19:00:00', '2013-04-29 20:00:00',
               '2013-04-29 21:00:00', '2013-04-29 22:00:00',
               '2013-04-29 23:00:00', '2013-04-30 00:00:00'],
              dtype='datetime64[ns]', length=697, freq='H')

然而，它每隔一小时生成一个间隔，即[0-1]，[2-3]，[4-5]，......但是，我需要的是像[0-1]这样的分区]，[1-2]，[2-3]，......我怎么能这样做？提前致谢。

期望的输出：

DatetimeIndex(['2013-04-01 00:00:00', '2013-04-01 01:00:00',
               '2013-04-01 01:00:00', '2013-04-01 02:00:00',
               '2013-04-01 02:00:00', '2013-04-01 03:00:00',
               '2013-04-01 03:00:00', '2013-04-01 04:00:00',
               '2013-04-01 04:00:00', '2013-04-01 05:00:00',
               ...
               '2013-04-29 19:00:00', '2013-04-29 20:00:00',
               '2013-04-29 20:00:00', '2013-04-29 21:00:00',
               '2013-04-29 21:00:00', '2013-04-29 22:00:00',
               '2013-04-29 22:00:00', '2013-04-29 23:00:00',
               '2013-04-29 23:00:00', '2013-04-30 00:00:00'],
              dtype='datetime64[ns]', length=697, freq='H')

Answer 1

这是单程

In [2249]: d = pd.date_range(start='2013-04-01', end='2013-04-30', freq='H')

In [2250]: pd.DatetimeIndex([v for p in zip(d, d[1:]) for v in p])
Out[2250]:
DatetimeIndex(['2013-04-01 00:00:00', '2013-04-01 01:00:00',
               '2013-04-01 01:00:00', '2013-04-01 02:00:00',
               '2013-04-01 02:00:00', '2013-04-01 03:00:00',
               '2013-04-01 03:00:00', '2013-04-01 04:00:00',
               '2013-04-01 04:00:00', '2013-04-01 05:00:00',
               ...
               '2013-04-29 19:00:00', '2013-04-29 20:00:00',
               '2013-04-29 20:00:00', '2013-04-29 21:00:00',
               '2013-04-29 21:00:00', '2013-04-29 22:00:00',
               '2013-04-29 22:00:00', '2013-04-29 23:00:00',
               '2013-04-29 23:00:00', '2013-04-30 00:00:00'],
              dtype='datetime64[ns]', length=1392, freq=None)

或者，

In [2252]: pd.DatetimeIndex(itertools.chain(*zip(d, d[1:])))
Out[2252]:
DatetimeIndex(['2013-04-01 00:00:00', '2013-04-01 01:00:00',
               '2013-04-01 01:00:00', '2013-04-01 02:00:00',
               '2013-04-01 02:00:00', '2013-04-01 03:00:00',
               '2013-04-01 03:00:00', '2013-04-01 04:00:00',
               '2013-04-01 04:00:00', '2013-04-01 05:00:00',
               ...
               '2013-04-29 19:00:00', '2013-04-29 20:00:00',
               '2013-04-29 20:00:00', '2013-04-29 21:00:00',
               '2013-04-29 21:00:00', '2013-04-29 22:00:00',
               '2013-04-29 22:00:00', '2013-04-29 23:00:00',
               '2013-04-29 23:00:00', '2013-04-30 00:00:00'],
              dtype='datetime64[ns]', length=1392, freq=None)

Answer 2

单行，直接执行：

In [237]: pd.date_range(start='2013-04-01', end='2013-04-30', freq='0.5H1U').round('1H')
Out[237]: 
DatetimeIndex(['2013-04-01 00:00:00', '2013-04-01 01:00:00',
               '2013-04-01 01:00:00', '2013-04-01 02:00:00',
               '2013-04-01 02:00:00', '2013-04-01 03:00:00',
               '2013-04-01 03:00:00', '2013-04-01 04:00:00',
               '2013-04-01 04:00:00', '2013-04-01 05:00:00',
               ...
               '2013-04-29 19:00:00', '2013-04-29 20:00:00',
               '2013-04-29 20:00:00', '2013-04-29 21:00:00',
               '2013-04-29 21:00:00', '2013-04-29 22:00:00',
               '2013-04-29 22:00:00', '2013-04-29 23:00:00',
               '2013-04-29 23:00:00', '2013-04-30 00:00:00'],
              dtype='datetime64[ns]', length=1392, freq=None)

我使用的频率为半小时加上一毫秒，因此四舍五入总是落在＆＃34;右侧＆＃34;。

在pandas中的指定时间间隔内为每个连续小时生成数据范围

2 个答案: