python - Numpy isnan()在浮点数组上失败(适用于pandas数据框)

我有一个浮点数数组(一些正常数字，一些nans)，它们是从对 Pandas 数据框的应用中得出的。

由于某种原因，numpy.isnan在此数组上失败，但是如下所示，每个元素都是浮点数，numpy.isnan在每个元素上正确运行，变量的类型肯定是numpy数组。

这是怎么回事？!

set([type(x) for x in tester])
Out[59]: {float}

tester
Out[60]:
array([-0.7000000000000001, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
   nan, nan], dtype=object)

set([type(x) for x in tester])
Out[61]: {float}

np.isnan(tester)
Traceback (most recent call last):

File "<ipython-input-62-e3638605b43c>", line 1, in <module>
np.isnan(tester)

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

set([np.isnan(x) for x in tester])
Out[65]: {False, True}

type(tester)
Out[66]: numpy.ndarray

最佳答案

np.isnan可以应用于 native dtype的NumPy数组(例如np.float64):

In [99]: np.isnan(np.array([np.nan, 0], dtype=np.float64))
Out[99]: array([ True, False], dtype=bool)

但是在应用于对象数组时引发TypeError:

In [96]: np.isnan(np.array([np.nan, 0], dtype=object))
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

由于您拥有 Pandas ，因此可以改为使用 pd.isnull －它可以接受对象或 native dtypes的NumPy数组:

In [97]: pd.isnull(np.array([np.nan, 0], dtype=float))
Out[97]: array([ True, False], dtype=bool)

In [98]: pd.isnull(np.array([np.nan, 0], dtype=object))
Out[98]: array([ True, False], dtype=bool)

请注意，None在对象数组中也被视为空值。