# Vector creation

As mentioned in Chapter 2, *Working with the NumPy Array As a First Step to SciPy*, SciPy depends on NumPy's main object's `ndarray`

data structure. You can look at one-dimensional arrays as vectors and vice versa (oriented points in an n-dimensional space). Consequently, a vector can be created via Numpy as follows:

>>> import numpy>>> vectorA = numpy.array([1,2,3,4,5,6,7])>>> vectorA

The output is shown as follows:

**array([1, 2, 3, 4, 5, 6, 7])**

We can also use already defined arrays to create a new candidate. Some examples were presented in the previous chapter. Here we can reverse the already created vector and assign it to a new one:

>>> vectorB = vectorA[::-1].copy()>>> vectorB

The output is shown as follows:

**array([7, 6, 5, 4, 3, 2, 1])**

Notice that in this example, we have to make a copy of the reverse of the elements of `vectorA`

and assign it to `vectorB`

. This way, by changing elements of `vectorB`

, the elements of `vectorA...`