Numpy isnan()在浮点数组上失败(适用于pandas数据框) [英] Numpy isnan() fails on an array of floats (from pandas dataframe apply)

问题描述

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

I have an array of floats (some normal numbers, some nans) that is coming out of an apply on a pandas dataframe.

由于某种原因，该数组上的numpy.isnan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，变量的类型肯定是一个numpy数组.

For some reason, numpy.isnan is failing on this array, however as shown below, each element is a float, numpy.isnan runs correctly on each element, the type of the variable is definitely a numpy array.

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

推荐答案

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

np.isnan can be applied to NumPy arrays of native dtype (such as 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会引发TypeError:

but raises TypeError when applied to object arrays:

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''

---

由于您拥有熊猫，因此可以使用 pd.isnull - -它可以接受对象或本机dtypes的NumPy数组:

---

Since you have Pandas, you could use pd.isnull instead -- it can accept NumPy arrays of object or native dtypes:

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.

Note that None is also considered a null value in object arrays.

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