In the following code below, I construct an array composed of two different arrays. This code example simulates the original problem's data, which is why there are two different arrays and they are accessed in this way. Once the array has been constructed, converted to numpy and transposed I want to access just the second list. However, once I have this second list, it is composed of list objects despite being rectangular (The values are in the format of (10,5)) Does anyone know why this happens? Is there some way to avoid it while still accessing the data in this way?

```
big_array = []

big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])
big_array.append([[0, 0],[0,0,0,0,0]])

big_array = np.asarray(big_array).transpose()
eval_array = big_array[1]
print(eval_array)
print(eval_array.shape)

```

Here is the output of the prints:

```
[list([0, 0, 0, 0, 0]) list([0, 0, 0, 0, 0]) list([0, 0, 0, 0, 0])
 list([0, 0, 0, 0, 0]) list([0, 0, 0, 0, 0]) list([0, 0, 0, 0, 0])
 list([0, 0, 0, 0, 0]) list([0, 0, 0, 0, 0]) list([0, 0, 0, 0, 0])
 list([0, 0, 0, 0, 0])]
(10,)

```

Clearly, the array in the above output is rectangular, but I suppose it has not been recognized as such.