Suppose I pass a 1D array:

```
>>> np.arange(0,20)
array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
       17, 18, 19])
>>> np.arange(0,20).shape
(20,)

```

into argwhere: 

```
>>> np.argwhere(np.arange(0,20)<10)
array([[0],
       [1],
       [2],
       [3],
       [4],
       [5],
       [6],
       [7],
       [8],
       [9]])
>>> np.argwhere(np.arange(0,20)<10).shape
(10, 1)

```

why has the result changed into a 2D array? What's the benefit of this?