当np.where抛出TypeError时，为什么np.vectorize在这里工作

Question

我有一个pandas DataFrame，其中一个名为myenum的列的值为0、1或2。我正在尝试将1和2转换为字符串，并使用Enum的.name属性来提供帮助。

我认为这是一个关于理解np.where与np.vectorize的本质的问题，因为它们与DataFrame系列有关。我很好奇为什么尝试使用np.where会抛出错误，而使用np.vectorize却能工作。我想从中学习，更好地理解DataFrames中的最佳矢量化实践。

import enum
import numpy as np
import pandas as pd
df = pd.DataFrame() # one column in this df is 'myenum', its values are either 0, 1, or 2
df['myenum'] = [0, 1, 2, 0, 0, 0, 2, 1, 0]

class MyEnum(enum.Enum):
First = 1
Second = 2
# this throws a TypeError - why?
df['myenum'] = np.where(
df['myenum'] > 0,
MyEnum(df['myenum']).name,
''
)
# whereas this, which seems pretty analagous, works.  what am i missing?
def vectorize_enum_value(x):
if x > 0:
return  MyEnum(x).name
return ''
vect = np.vectorize(vectorize_enum_value)
df['myenum'] = vect(df['myenum'])

Answer 1

来自where表达式的完整回溯是：

Traceback (most recent call last):
File "/usr/lib/python3.8/enum.py", line 641, in __new__
return cls._value2member_map_[value]
TypeError: unhashable type: 'Series'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<ipython-input-27-16f5edc71240>", line 3, in <module>
MyEnum(df['myenum']).name,
File "/usr/lib/python3.8/enum.py", line 339, in __call__
return cls.__new__(cls, value)
File "/usr/lib/python3.8/enum.py", line 648, in __new__
if member._value_ == value:
File "/usr/local/lib/python3.8/dist-packages/pandas/core/generic.py", line 1537, in __nonzero__
raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

它是通过将整个系列赋予MyEnum:而产生的

In [30]: MyEnum(df['myenum'])
Traceback (most recent call last):
File "/usr/lib/python3.8/enum.py", line 641, in __new__
return cls._value2member_map_[value]
TypeError: unhashable type: 'Series'
...

问题根本不在于where。

如果我们为where提供一个有效的字符串列表，它就可以正常工作：

In [33]: np.where(
...:     df['myenum'] > 0,
...:     [vectorize_enum_value(x) for x in df['myenum']],
...:     ''
...:     )
Out[33]: 
array(['', 'First', 'Second', '', '', '', 'Second', 'First', ''],
dtype='<U6')

第二个论点，列表理解与vectorize基本相同。

CCD_ 6是一个函数；Python在传入函数参数之前对其进行求值。因此，每个参数都必须有效。where不是像apply甚至vectorize那样的迭代器。