在熊貓中的指定時間間隔內每連續一小時生成一個數據範圍

Question

我試圖在使用熊貓的預定義日期集合期間爲每個小時生成一組時間間隔。我已經使用：

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，它產生的時間間隔，每隔小時，即[0-1]，[2-3]，[4-5]，...不過，我需要什麼是像[0-1]，[1-2]，[2-3]這樣的分區，我該怎麼做？提前致謝。

所需的輸出：

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

這裏有一種方法

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

一行代碼，直接做：

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) 

我使用的頻率爲半小時，加上一毫秒，因此舍入總是落在「右側」。