How to prevent np.where from turning 0 into ‘0’?

I want to create an array with np.where that has strings and 0s in it. So usually its dtype would be ‘object’. Minimal example:

A = np.array([[1,2,1],[2,1,2],[1,1,2]])
x = np.where(A==1,0,'hello')

As a result I get

array([['0', 'hello', '0'],
       ['hello', '0', 'hello'],
       ['0', '0', 'hello']], dtype='<U11')

I would like those ‘0’s to be 0s. Since np.where has no argument for dtype, I don’t know how to do this except by replacing them afterwards. There has to be a better way to do this.

Answer

You could use an object array as first input values for where:

x = np.where(A==1, np.zeros_like(A).astype(object), 'hello')

Output:

array([[0, 'hello', 0],
       ['hello', 0, 'hello'],
       [0, 0, 'hello']], dtype=object)