Np.newaxis adds an axis to Numpy.ndarray (multidimensional array)

type(np.newaxis)NoneType

Np.newaxis in use and functionally equivalent to none, in fact, is an alias of none.

1. Np.newaxis's Practical

>> x = np.arange(3)>> xarray([0, 1, 2])>> x.shape(3,)>> x[:, np.newaxis]array([[0], [1], [2]])>> x[:, None]array([[0], [1], [2]])>> x[:, np.newaxis].shape (3, 1)

2. A row vector is returned when a column of a multidimensional array is indexed

>>> X = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])>>> X[:, 1]array([2, 6, 10]) % 这里是一个行>>> X[:, 1].shape % X[:, 1] 的用法完全等同于一个行，而不是一个列，(3, )

So, a correct way to index is:

>>>X[:, 1][:, np.newaxis]array([[2],      [6],      [10]])

If you want to make the concatenation (cascade) of the second and fourth columns:

>>>X_sub = np.hstack([X[:, 1][:, np.newaxis], X[:, 3][:, np.newaxis]])            % hstack：horizontal stack，水平方向上的层叠>>>X_subarray([[2, 4] [6, 8] [10, 12]])

Np.newaxis adds an axis to Numpy.ndarray (multidimensional array)