创建一个布尔数组，将numpy元素与None进行比较

I have a numpy array with dtype=object, and I want to create a boolean array identifying which elements are None. But it looks like None behaves differently...

我有一个带有dtype = object的numpy数组，我想创建一个布尔数组来标识哪些元素是None。但看起来没有表现出不同的......

a = np.array(['Duck','Duck','Duck','Goose',None,1,2,3,1,3,None,4])
print a == 'Duck'
print a == 3
print a == None

which results in

结果

[ True  True  True False False False False False False False False False]
[False False False False False False False  True False  True False False]
False

Is there an "numpythonic" way to get a boolean array of the None elements? I can use

是否有一种“numpythonic”方式来获取None元素的布尔数组？我可以用

np.array([x is None for x in a])

but this seems like there should be a better way.

但这似乎应该有更好的方法。

1 个解决方案

#1

You can use numpy.equal:

你可以使用numpy.equal：

In [20]: np.equal(a, None)
Out[20]: 
array([False, False, False, False,  True, False, False, False, False,
       False,  True, False], dtype=bool)