How To Filter Out Subarrays Which Contain Nan's?

Let's assume an array of shape (n,5,2) which contains NaNs at random places, generated by the following code: n = 10 arr = np.random.rand(n, 5, 2) # replace some values by nan arr

Solution 1:

No need to reshape anything:

has_nans = np.isnan(arr).any(axis=(-1,-2))
has_nans 
array([False, False, False,  True,  True,  True, False, False, False,  True], dtype=bool)

>>> arr = arr[~has_nans]
>>> arr.shape
(6, 5, 2)

Older versions of numpy you will need to do something like the following:

has_nans = np.isnan(arr).any(axis=-1).any(axis=-1)

Solution 2:

This is a 1 liner:

new = arr[~np.isnan(arr).any((-1,-2))]

printnew.shape
Out[10]: (5, 5, 2)