How do I can get array like this array([[0.37454012], [0.95071431], [0.73199394]]) using Numpy

Question

I have a function that takes 2 parameters and returns a shape of an array. where the function that will create a Numpy array of a given shape with random values. The output should be like this: array([[0.37454012], [0.95071431], [0.73199394]]), but I got it like this: arrayarray([[0.37454012, 0.95071431, 0.73199394]])).

What is the methoud that I can use to return it like this: ([[0.37454012], [0.95071431], [0.73199394]])

For example, initialise_array(3,1) will return an array of dimensions (3,1) that can look like this:

array([[0.37454012], [0.95071431], [0.73199394]])

My code:

def initialise_array(n_features, n_observations): 
    shape = np.random.rand(n_features, n_observations) 
    n_shape = shape.reshape(n_observations, n_features) 
    return n_shape

The output looks like array([[0.85546058, 0.70365786, 0.47417383]]) but I need to match the this array([[0.37454012], [0.95071431], [0.73199394]])

Does this answer your question? [How do I can get array like this array(\[\[1\], \[2\], \[3\]\]) using Numpy](https://stackoverflow.com/questions/71574607/how-do-i-can-get-array-like-this-array1-2-3-using-numpy) — Michael Szczesny, Mar 22 '22 at 22:11
Please do not repost your own question that already has an answer. — Michael Szczesny, Mar 22 '22 at 22:12
doesn't work I need the output looks like this array ([[1],[2],[3]]), not like this array([[1, 2,3]]), shell i use for loop ? — Sa'adoon, Mar 22 '22 at 22:14

score 0 · Answer 1 · answered Mar 22 '22 at 22:07

If I understand correctly, just get rid of your reshape call

def initialise_array(n_features, n_observations): 
    shape = np.random.rand(n_features, n_observations) 
    return shape

Output:

>>> initialise_array(3, 1)
array([[0.38454951],
       [0.61060765],
       [0.84899489]])

score 0 · Answer 2 · answered Mar 23 '22 at 07:30

The first thing to note is that parameters passed to np.random.rand define just the shape of the array to be created.

So much shorter and simpler code than yours is:

def initialise_array(n_features, n_observations): 
    return np.random.rand(n_features, n_observations)

When you call this function as: initialise_array(3, 1) you will get an array with 3 rows and a single column. Just as you wish.

And a remark about your code:

It is misleading in the way you use variable names.

Note that what you save under shape variable is not any shape, but an array (of the shape passed with parameters).

How do I can get array like this array([[0.37454012], [0.95071431], [0.73199394]]) using Numpy

2 Answers2