dalmeida13 - 4 years ago 411
Python Question

# Using np.where to find matching row in 2D array

I would like to know how I use

`np.where`
with 2D array

I have the following array:

``````arr1 = np.array([[ 3.,  0.],
[ 3.,  1.],
[ 3.,  2.],
[ 3.,  3.],
[ 3.,  6.],
[ 3.,  5.]])
``````

I want to find this array:

``````arr2 = np.array([3.,0.])
``````

But when I use
`np.where()`
:

``````np.where(arr1 == arr2)
``````

It returns:

``````(array([0, 0, 1, 2, 3, 4, 5]), array([0, 1, 0, 0, 0, 0, 0]))
``````

I can't understand what it means. Can someone explain this for me?

You probably wanted all rows that are equal to your `arr2`:

``````>>> np.where(np.all(arr1 == arr2, axis=1))
(array([0], dtype=int64),)
``````

Which means that the first row (zeroth index) matched.

The problem with your approach is that numpy broadcasts the arrays (visualized with `np.broadcast_arrays`):

``````>>> arr1_tmp, arr2_tmp = np.broadcast_arrays(arr1, arr2)
>>> arr2_tmp
array([[ 3.,  0.],
[ 3.,  0.],
[ 3.,  0.],
[ 3.,  0.],
[ 3.,  0.],
[ 3.,  0.]])
``````

and then does elementwise-comparison:

``````>>> arr1 == arr2
array([[ True,  True],
[ True, False],
[ True, False],
[ True, False],
[ True, False],
[ True, False]], dtype=bool)
``````

and `np.where` then gives you the coordinates of every `True`:

``````>>> np.where(arr1 == arr2)
(array([0, 0, 1, 2, 3, 4, 5], dtype=int64),
array([0, 1, 0, 0, 0, 0, 0], dtype=int64))
#       ^---- first match (0, 0)
#          ^--- second match (0, 1)
#             ^--- third match (1, 0)
#  ...
``````

Which means `(0, 0)` (first row left item) is the first `True`, then `0, 1` (first row right item), then `1, 0` (second row, left item), ....

If you use `np.all` along the first axis you get all rows that are completly equal:

``````>>> np.all(arr1 == arr2, axis=1)
array([ True, False, False, False, False, False], dtype=bool)
``````

Can be better visualized if one keeps the dimensions:

``````>>> np.all(arr1 == arr2, axis=1, keepdims=True)
array([[ True],
[False],
[False],
[False],
[False],
[False]], dtype=bool)
``````
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