Question: I have a 3D nested list constructed like this:

```
[[[1,1],[2,1],[2,2],[1,2]],[[-1,-1],[-2,-1],[-2,-2],[-1,-2]]]

```

and I want to concat to that `[[0,0]]` to get this result:

```
[[[1,1],[2,1],[2,2],[1,2]],[[-1,-1],[-2,-1],[-2,-2],[-1,-2]],[[0,0]]]

```

I tried to use `numpy.append` and `column_stack` methods, but it complains about dimension mismatch. How to do that right?

Answer: 
The problem is that once you have a `numpy` array with shape `(2, 4, 2)`, you cannot really append another array with shape `(1, 1, 2)` unless you treat lists as objects (i.e. you are appending an element to an array of size `2` so that in the end you have an array of size `3`).

If you have a `numpy` array of `list` objects you won't be able to benefit from most of the functionality provided by `numpy` so perhaps explain in a bit more detail what exactly you are trying to achieve here.

```py
>>> a = np.array([[[1,1],[2,1],[2,2],[1,2]],[[-1,-1],[-2,-1],[-2,-2],[-1,-2]]])
>>> b = np.array([[[0, 0]]])
>>> a.shape, b.shape
((2, 4, 2), (1, 1, 2))
>>> c = np.array(a.tolist() + b.tolist())
>>> c
array([list([[1, 1], [2, 1], [2, 2], [1, 2]]),
       list([[-1, -1], [-2, -1], [-2, -2], [-1, -2]]), list([[0, 0]])],
      dtype=object)
>>> c.shape
(3,)
>>> c.tolist()
[[[1, 1], [2, 1], [2, 2], [1, 2]],
 [[-1, -1], [-2, -1], [-2, -2], [-1, -2]],
 [[0, 0]]]

```

The last value is the list you seem to be looking for. You don't have to go through this process with `numpy` to get it and can simply `append` as others have suggested.
guess what, I can just use default `append` function; I didn't know that function is not returning the new array