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 ind
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)]
Since x!=x
returns the same boolean array with np.isnan(x)
(because np.nan!=np.nan
would return True
), you could also write:
np.argwhere(x!=x)
However, I still recommend writing np.argwhere(np.isnan(x))
since it is more readable. I just try to provide another way to write the code in this answer.