How can I differentiate between column vectors and row vectors using Python

Question

Hi all, my question is simple. All I wanted to know was if there was a recommended way which is used to differentiate between the column vectors and the row vectors using Python?

Up until now, I use SciPy and NumPy and I know when I have to give a single vector something like this:

from numpy import *
Vector = array([5,6,7])

This will not tell me if it's a column or a row vector, correct?

And also, check out the following piece of code:

array([5,6,7]) == array([5,6,7]).transpose()
True

This is not possible, right? Differentiation is not needed for the functions on the mentioned modules is what I already know of.

Consider this, outer(a,b) or say even a.dot(b) - But then it would be nicer if I could differentiate it at my own convenience, don't you think?

All help appreciated!

Answer 1

Hi, good question. What you can do to fix this is to make it explicit to forcing on the dimension to the array. 

Check out the following piece of code for clarity:

>>> a = np.array([5, 6, 7])
>>> a
array([5, 6, 7])
>>> a.transpose()
array([5, 6, 7])
>>> a.dot(a.transpose())
14

 Now, you use the column vector for specificity and you make sure that it is forced upon and used.

Check out the below code:

>>> a.shape = (3,1)
>>> a
array([[5],
       [6],
       [7]])
>>> a.transpose()
array([[5, 6, 7]])
>>> a.dot(a.transpose())
array([[1, 2, 3],
       [2, 4, 6],
       [3, 6, 9]])

Hope this helped!