【问题标题】:selecting observation of datetime64[ns] type in particular time range在特定时间范围内选择对 datetime64[ns] 类型的观察
【发布时间】:2014-01-21 06:55:24
【问题描述】:

我有一个熊猫数据框(dfnew),其中一列(时间戳)是datetime64[ns] 类型。现在我想看看在特定时间范围内有多少观察,比如说 10:00:00 到 12:00:00。

    dfnew['timestamp'] = dfnew['timestamp'].astype('datetime64[ns]')
    dfnew['timestamp]
0    2013-12-19 09:03:21.223000
1    2013-12-19 11:34:23.037000
2    2013-12-19 11:34:23.050000
3    2013-12-19 11:34:23.067000
4    2013-12-19 11:34:23.067000
5    2013-12-19 11:34:23.067000
6    2013-12-19 11:34:23.067000
7    2013-12-19 11:34:23.067000
8    2013-12-19 11:34:23.067000
9    2013-12-19 11:34:23.080000
10   2013-12-19 11:34:23.080000
11   2013-12-19 11:34:23.080000
12   2013-12-19 11:34:23.080000
13   2013-12-19 11:34:23.080000
14   2013-12-19 11:34:23.080000
15   2013-12-19 11:34:23.097000
16   2013-12-19 11:34:23.097000
17   2013-12-19 11:34:23.097000
18   2013-12-19 11:34:23.097000
19   2013-12-19 11:34:23.097000
Name: timestamp

    dfnew['Time']=dfnew['timestamp'].map(Timestamp.time)
    t1 = datetime.time(10, 0, 0)
    t2 = datetime.time(12, 0, 0)
    print len(dfnew[t1<dfnew["Time"]<t2])

这会产生一个错误TypeError: can't compare datetime.time to Series。 我是熊猫数据框的新手。我想我在这里犯了一个非常愚蠢的错误。任何帮助表示赞赏。

【问题讨论】:

    标签: python pandas python-datetime


    【解决方案1】:

    您可以使用 DatetimeIndex indexer_between_time 方法,因此这里使用它的一个技巧是将 Series / 列传递给 DatetimeIndex 构造函数:

    from datetime import time
    
    # s is your datetime64 column
    
    In [11]: pd.DatetimeIndex(s).indexer_between_time(time(10), time(12))
    Out[11]: 
    array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19])
    

    这会得到10到12(含*)之间时间的位置,所以使用iloc过滤:

    In [12]: s.iloc[pd.DatetimeIndex(s).indexer_between_time(time(10), time(12))]
    Out[12]: 
    1    2013-12-19 11:34:23.037000
    2    2013-12-19 11:34:23.050000
    3    2013-12-19 11:34:23.067000
    4    2013-12-19 11:34:23.067000
    5    2013-12-19 11:34:23.067000
    6    2013-12-19 11:34:23.067000
    7    2013-12-19 11:34:23.067000
    8    2013-12-19 11:34:23.067000
    9    2013-12-19 11:34:23.080000
    10   2013-12-19 11:34:23.080000
    11   2013-12-19 11:34:23.080000
    12   2013-12-19 11:34:23.080000
    13   2013-12-19 11:34:23.080000
    14   2013-12-19 11:34:23.080000
    15   2013-12-19 11:34:23.097000
    16   2013-12-19 11:34:23.097000
    17   2013-12-19 11:34:23.097000
    18   2013-12-19 11:34:23.097000
    19   2013-12-19 11:34:23.097000
    Name: timestamp, dtype: datetime64[ns]
    

    * include_startinclude_endindexer_between_time 的可选布尔参数。

    【讨论】:

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