Question

我有一个大的DataFrame，我想切片，以便我可以对切片的数据帧执行一些计算，以便在原始值中更新值。另外，我正在按照索引中可能不存在的开始和结束时间对数据帧进行切片。下面是一个简化的示例，但我实际上想要根据不同的计算更新多个列。

In [1]: df
Out[1]:

                         A        B         C
TIME
2014-01-02 14:00:00 -1.172285  1.706200    NaN
2014-01-02 14:05:00  0.039511 -0.320798    NaN
2014-01-02 14:10:00 -0.192179 -0.539397    NaN
2014-01-02 14:15:00 -0.475917 -0.280055    NaN
2014-01-02 14:20:00  0.163376  1.124602    NaN
2014-01-02 14:25:00 -2.477812  0.656750    NaN

我已经尝试了以下所有语句来创建sdf作为我的时间范围的视图：

start = datetime.strptime('2014-01-02 14:07:00', '%Y-%m-%d %H:%M:%S')
end = datetime.strptime('2014-01-02 14:22:00', '%Y-%m-%d %H:%M:%S')

sdf = df[start:end]
sdf = df[start < df.index < end]
sdf = df.ix[start:end]
sdf = df.loc[start:end]
sdf = df.truncate(before=start, after=end, copy=False)

sdf[C] == 100

大多数人都会返回一份副本，然后收到一个SettingWithCopyWarning警告。 loc函数表示索引与datetime不兼容。这是我应该做的事情。更新切片后我想要的结果是：

In [1]: df
Out[1]:

                         A        B         C
TIME
2014-01-02 14:00:00 -1.172285  1.706200    NaN
2014-01-02 14:05:00  0.039511 -0.320798    NaN
2014-01-02 14:10:00 -0.192179 -0.539397    100
2014-01-02 14:15:00 -0.475917 -0.280055    100
2014-01-02 14:20:00  0.163376  1.124602    100
2014-01-02 14:25:00 -2.477812  0.656750    NaN

任何人都可以建议一个方法吗？我是以错误的方式接近这个吗？

由于

Answer 1

一种方法是使用loc并将条件包装在括号中并使用按位曝光器&，在比较值数组而不是单个值时，需要按位运算符，由于运算符优先级，需要括号。然后我们可以使用它来使用loc执行标签选择，并设置＆＃39; C＆＃39;列如此：

In [15]:

import datetime as dt
start = dt.datetime.strptime('2014-01-02 14:07:00', '%Y-%m-%d %H:%M:%S')
end = dt.datetime.strptime('2014-01-02 14:22:00', '%Y-%m-%d %H:%M:%S')
df.loc[(df.index > start) & (df.index < end), 'C'] = 100
df
Out[15]:
                            A         B    C
TIME                                        
2014-01-02 14:00:00 -1.172285  1.706200  NaN
2014-01-02 14:05:00  0.039511 -0.320798  NaN
2014-01-02 14:10:00 -0.192179 -0.539397  100
2014-01-02 14:15:00 -0.475917 -0.280055  100
2014-01-02 14:20:00  0.163376  1.124602  100
2014-01-02 14:25:00 -2.477812  0.656750  NaN

如果我们看一下您尝试的每种方法以及它们为什么不起作用：

sdf = df[start:end] #  will raise KeyError if start and end are not present in index
sdf = df[start < df.index < end] #  will raise ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all(), this is because you are comparing arrays of values not a single scalar value
sdf = df.ix[start:end] # raises KeyError same as first example
sdf = df.loc[start:end] #  raises KeyError same as first example
sdf = df.truncate(before=start, after=end, copy=False) # generates correct result but operations on this will raise SettingWithCopyWarning as you've found

修改

您可以将sdf设置为掩码，并将其与loc一起用来设置您的＆＃39; C＆＃39;柱：

In [7]: import datetime as dt start = dt.datetime.strptime('2014-01-02 14:07:00', '%Y-%m-%d %H:%M:%S') end = dt.datetime.strptime('2014-01-02 14:22:00', '%Y-%m-%d %H:%M:%S') sdf = (df.index > start) & (df.index < end) df.loc[sdf,'C'] = 100 df Out[7]: A B C TIME 2014-01-02 14:00:00 -1.172285 1.706200 NaN 2014-01-02 14:05:00 0.039511 -0.320798 NaN 2014-01-02 14:10:00 -0.192179 -0.539397 100 2014-01-02 14:15:00 -0.475917 -0.280055 100 2014-01-02 14:20:00 0.163376 1.124602 100 2014-01-02 14:25:00 -2.477812 0.656750 NaN

Pandas：按日期时间切片数据帧（可能不存在）和返回视图

1 个答案: