如何在包含字符串的 numpy ndarray 中檢查 NaN

Question

通常我可以使用 numpy.isnan() 檢查 NaN：

import numpy as np

arr1 = np.array([[1, 2], [3, 4], [np.nan, 5]])
print(type(arr1))
print(np.isnan(arr1))

<class 'numpy.ndarray'>
[[False False]
 [False False]
 [ True False]]

但是，對於包含字符串的數組，我該如何實現呢？

arr2 = np.array([[1, 2], [3, 4], [np.nan, 5], ['high', 'low']])
print(type(arr2))
print(np.isnan(arr2))

<class 'numpy.ndarray'>

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-19-4a4a4bc72076> in <module>
      1 array = np.array([[1, 2], [3, 4], [np.nan, 5], ['high', 'low']])
      2 print(type(array))
----> 3 print(np.isnan(array))

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''

Answer 1

正如評論者所建議的那樣，在數組中包含字符串導致所有元素都被靜默地強制為字符串，包括現在是 'nan' 的 np.nan 值，可以通過 arr2==nan 找到：

print(arr1=='nan')

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