Question

My problem is that I've got this array:

np.array([0.0, 0.0, -1.2, -1.2, -3.4, -3.4, -4.5, -4.5])

and I want to convert the elements to array like this:

np.array([[0.0], [0.0], [-1.2], [-1.2], [-3.4], [-3.4], [-4.5], [-4.5]])

So is there a loop or a numpy function that I could use to do this task?

Answer 1

Or simply:

arr[:,None]

# array([[ 0. ],
#        [ 0. ],
#        [-1.2],
#        [-1.2],
#        [-3.4],
#        [-3.4],
#        [-4.5],
#        [-4.5]])

Answer 2

You can use a list comprehension:

>>> a1 = np.array([0.0, 0.0, -1.2, -1.2, -3.4, -3.4, -4.5, -4.5])
>>> np.array([[x] for x in a1])
array([[ 0. ],
       [ 0. ],
       [-1.2],
       [-1.2],
       [-3.4],
       [-3.4],
       [-4.5],
       [-4.5]])
>>>

Answer 3

Isn't this just a reshape operation from row to column vector?

In [1]: import numpy as np
In [2]: x = np.array([0.0, 0.0, -1.2, -1.2, -3.4, -3.4, -4.5, -4.5])
In [3]: np.reshape(x, (-1,1))
Out[3]: 
array([[ 0. ],
       [ 0. ],
       [-1.2],
       [-1.2],
       [-3.4],
       [-3.4],
       [-4.5],
       [-4.5]])

Answer 4

使用numpy函数可以通过多种方式实现此目的：

np.expand_dims - 显式选项

>>> import numpy as np
>>> a = np.array([0.0, 0.0, -1.2, -1.2, -3.4, -3.4, -4.5, -4.5])

>>> np.expand_dims(a, axis=1)
array([[ 0. ], [ 0. ], [-1.2], [-1.2], [-3.4], [-3.4], [-4.5], [-4.5]])

使用np.newaxis切片（None的别名）

>>> np.array(a)[:, np.newaxis]
array([[ 0. ], [ 0. ], [-1.2], [-1.2], [-3.4], [-3.4], [-4.5], [-4.5]])
>>> np.array(a)[:, None]
array([[ 0. ], [ 0. ], [-1.2], [-1.2], [-3.4], [-3.4], [-4.5], [-4.5]])

除了手动添加axis之外，您还可以使用一些默认方式创建多维数组，然后交换轴，例如使用np.transpose，但您也可以使用np.swapaxes或np.reshape：

np.array，ndmin = 2

>>> np.array([0.0, 0.0, -1.2, -1.2, -3.4, -3.4, -4.5, -4.5], ndmin=2).T
array([[ 0. ], [ 0. ], [-1.2], [-1.2], [-3.4], [-3.4], [-4.5], [-4.5]])

np.atleast_2d和

>>> np.atleast_2d(a).swapaxes(1, 0)
array([[ 0. ], [ 0. ], [-1.2], [-1.2], [-3.4], [-3.4], [-4.5], [-4.5]])

how to convert items of array into array themselves Python

4 个答案: