1

I want an array that looks like this,

array([array([[1, 1], [2, 2]]), array([3, 3])], dtype=object)

I can make an empty array and then assign elements one by one like this,

z = [np.array([[1,1],[2,2]]), np.array([3,3])]
x = np.empty(shape=2, dtype=object)
x[0], x[1] = z

I thought if this possible then so should be this: x = np.array(z, dtype=object), but that gets me the error: ValueError: could not broadcast input array from shape (2,2) into shape (2).

So is the way given above the only way to make a ragged numpy array? Or, is there a nice one line constructor/function we can can call to make the array x from above.

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2
  • Does this answer your question? Python numpy array of numpy arrays Commented Jun 11, 2020 at 1:56
  • No, I am not looking to append or concatenate a row/column. I want an array of other array objects which happen to be different shapes as shown in the example array x. Commented Jun 11, 2020 at 2:16
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