# How to create an integer numpy 2darray of indexes from ndarray where elements are integers?

I’m trying to create an 2d numpy array in shape n x k where n is the dimension of the ndarray given and k is the amount of elements from the ndarray that are integers. Each row in the returned array should contain the indexes at which the condition holds at the relevant dimension.
For example, the ndarray is:

``````array([[ 0.        , -0.36650892, -0.51839849,  4.55566517,  4.        ],
[ 5.21031078,  6.29935488,  8.29787346,  7.03293348,  8.74619707],
[ 9.36992033, 11.        , 11.88485714, 12.98729128, 13.98447014],
[14.        , 16.71828376, 16.15909201, 17.86503506, 19.12607872]])
``````

Again, the condition is if the element is an integer so the returned array should be:

``````array([[0,0,2,3],
[0,4,1,0]])
``````

Note that for the 0th row we want the 0th and 4th elements so we get `[0,0,....],[0,4,...]` and so on.
I thought about creating a new array at the same shape as `arr` with True at the integer element positions and False elsewhere. Not sure where to proceed with this though.
Any help would be appreciated.

### >Solution :

Assuming `a` the input array, you can compare to the rounded values to identify the integers, use `numpy.where` to get their indices and `np.vstack` to form the final array:

``````np.vstack(np.where(a==a.round()))
``````

output:

``````array([[0, 0, 2, 3],
[0, 4, 1, 0]])
``````