numpy array: IndexError: too many indices for array

Question

This works:

>>> a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
>>> a[: , 2]
array([ 3,  7, 11])

This doesn\'t

Answer 1

Numpy ndarrays are meant for all elements to have the same length. In this case, your second array doesn't contain lists of the same length, so it ends up being a 1-D array of lists, as opposed to a "proper" 2-D array.

From the Numpy docs on N-dimensional arrays:

An ndarray is a (usually fixed-size) multidimensional container of items of the same type and size.

a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
a.shape # (3,4)
a.ndim # 2

b = np.array([[1,2,3,4], [5,6,7,8], [9,10,11]])
b.shape # (3,)
b.ndim # 1

This discussion may be useful.

Answer 2

It's simple to see what the problem is. Try,

>>> a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
>>> a.shape

and then

>>>a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11]])
>>> a.shape

and you will see the problem yourself, that in case two, shape is (3,).Hence the too many indices.

Answer 3

The first array has shape (3,4) and the second has shape (3,). The second array is missing a second dimension. np.array is unable to use this input to construct a matrix (or array of similarly-lengthed arrays). It is only able to make an array of lists.

>>> a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])

>>> print(a)
[[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]]

>>> print(type(a))
<class 'numpy.ndarray'>


>>> b = np.array([[1,2,3,4], [5,6,7,8], [9,10,11]])

>>> print(b)
[list([1, 2, 3, 4]) list([5, 6, 7, 8]) list([9, 10, 11])]

>>> print(type(b))
<class 'numpy.ndarray'>

So they are both Numpy arrays, but only the first can be treated as a matrix with two dimensions.