CODEWITHSUNDEEP
pythonpython-3.xnumpy
Elie Dumas-Lefebvre
Elie Dumas-Lefebvre

Reputation: 43

how to convert items of array into array themselves Python

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?

Upvotes: 4

Views: 264

Answers (4)

MSeifert
MSeifert

Reputation: 152795

There are several ways to achieve this with functions:

  • np.expand_dims - the explicit option

    >>> 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]])

  • slicing with np.newaxis (which is an alias for None)

    >>> 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]])

Instead of adding an axis manually you can also use some default ways to create a multidimensional array and then swap the axis, for example with np.transpose but you could also use np.swapaxes or np.reshape:

  • np.array with 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 and 

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

Upvotes: 1

akuiper
akuiper

Reputation: 215117

Or simply:

arr[:,None]

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

Upvotes: 13

zwol
zwol

Reputation: 140836

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]])

Upvotes: 6

Bahrom
Bahrom

Reputation: 4862

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]])
>>>

Upvotes: 7

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