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Say now I have a numpy array which is defined as,
[[1,2,3,4], [2,3,NaN,5], [NaN,5,2,3]] Now I want to have a list that contains all the indices of the missing values, which is [(1,2),(2,0)] at this case.
Is there any way I can do that?
849
To check for NaN values in a Numpy array you can use the np. isnan() method. This outputs a boolean mask of the size that of the original array. The output array has true for the indices which are NaNs in the original array and false for the rest.
The math. isnan(value) method takes a number value as input and returns True if the value is a NaN value and returns False otherwise. Therefore we can check if there a NaN value in a list or array of numbers using the math. isnan() method.
nonzero() function is used to Compute the indices of the elements that are non-zero. It returns a tuple of arrays, one for each dimension of arr, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values in the array can be obtained with arr[nonzero(arr)] .
np.isnan combined with np.argwhere
x = np.array([[1,2,3,4], [2,3,np.nan,5], [np.nan,5,2,3]]) np.argwhere(np.isnan(x)) output:
array([[1, 2], [2, 0]]) You can use np.where to match the boolean conditions corresponding to Nan values of the array and map each outcome to generate a list of tuples.
>>>list(map(tuple, np.where(np.isnan(x)))) [(1, 2), (2, 0)] If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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