如何根据已经生成的日期范围序列对特定日期进行分类（排序）？

Question

我列出了一个日期序列：

import pandas as pd

daterange2016 = pd.date_range("2016-04-25 00:00:00", "2016-04-29 21:00:00", freq="30min")

但是，我需要一个函数来获取日期时间，并知道时间属于哪个间隔。我不想改变间隔。我该怎么做？你知道吗

类似于（这里是一个伪代码）：

def datetimesorter(givendate):
    if givendate:
       df['pd_time_interval_that_givendate_belongs_to'] = givendate

提前谢谢你的帮助

更新：我想出了这个，它的工作，但我不会删除的问题，只是以防万一，它有助于某人

def daterangefinder(datetime):
    for intervals in daterange2016:
        if intervals <= datetime < intervals+1:
            return intervals
        else:
            pass

Answer 1

IIUC您可以尝试：

import pandas as pd

daterange2016 = pd.date_range("2016-04-25 00:00:00", "2016-04-25 05:00:00", freq="30min")
print daterange2016
DatetimeIndex(['2016-04-25 00:00:00', '2016-04-25 00:30:00',
               '2016-04-25 01:00:00', '2016-04-25 01:30:00',
               '2016-04-25 02:00:00', '2016-04-25 02:30:00',
               '2016-04-25 03:00:00', '2016-04-25 03:30:00',
               '2016-04-25 04:00:00', '2016-04-25 04:30:00',
               '2016-04-25 05:00:00'],
              dtype='datetime64[ns]', freq='30T')

df = pd.DataFrame(daterange2016, columns=['d1'])

df['d2']= df.d1.shift(-1)
print df
                    d1                  d2
0  2016-04-25 00:00:00 2016-04-25 00:30:00
1  2016-04-25 00:30:00 2016-04-25 01:00:00
2  2016-04-25 01:00:00 2016-04-25 01:30:00
3  2016-04-25 01:30:00 2016-04-25 02:00:00
4  2016-04-25 02:00:00 2016-04-25 02:30:00
5  2016-04-25 02:30:00 2016-04-25 03:00:00
6  2016-04-25 03:00:00 2016-04-25 03:30:00
7  2016-04-25 03:30:00 2016-04-25 04:00:00
8  2016-04-25 04:00:00 2016-04-25 04:30:00
9  2016-04-25 04:30:00 2016-04-25 05:00:00
10 2016-04-25 05:00:00                 NaT

date = pd.to_datetime('2016-04-25 02:15:08')
print date
2016-04-25 02:15:08

print (df.d1 < date) & (df.d2 > date)
0     False
1     False
2     False
3     False
4      True
5     False
6     False
7     False
8     False
9     False
10    False
dtype: bool

print df[(df.d1 < date) & (df.d2 > date)].d1
4   2016-04-25 02:00:00
Name: d1, dtype: datetime64[ns]

如果需要将date添加到新列d3，请使用^{}：

df.loc[(df.d1 < date) & (df.d2 > date), 'd3'] =  date
print df
                    d1                  d2                  d3
0  2016-04-25 00:00:00 2016-04-25 00:30:00                 NaT
1  2016-04-25 00:30:00 2016-04-25 01:00:00                 NaT
2  2016-04-25 01:00:00 2016-04-25 01:30:00                 NaT
3  2016-04-25 01:30:00 2016-04-25 02:00:00                 NaT
4  2016-04-25 02:00:00 2016-04-25 02:30:00 2016-04-25 02:15:08
5  2016-04-25 02:30:00 2016-04-25 03:00:00                 NaT
6  2016-04-25 03:00:00 2016-04-25 03:30:00                 NaT
7  2016-04-25 03:30:00 2016-04-25 04:00:00                 NaT
8  2016-04-25 04:00:00 2016-04-25 04:30:00                 NaT
9  2016-04-25 04:30:00 2016-04-25 05:00:00                 NaT
10 2016-04-25 05:00:00                 NaT                 NaT