3.7 Append

We have already seen how to build a Numpy array from a sequence of values.

# Load the Numpy package, and rename to "np"
import numpy as np

One way to create an array is to make a sequence of values, such as a list, and pass these to the np.array function, like this:

my_list = [1.1, 2.2, 3.2, 2.1]
my_array = np.array(my_list)
my_array

array([1.1, 2.2, 3.2, 2.1])

Here we create the full 4 value array in one call to np.array.

Another way make an array is to build it up one value at a time.

To do this, I can start with an empty array, like this:

an_empty_list = []
a = np.array(an_empty_list)
a

array([], dtype=float64)

Now imagine I want to build up the same array as I did above. I can append each value to the array, using the np.append function.

As usual, you can check what the np.append function does by making a new cell in the notebook, and typing np.append? followed by Enter. This will show you the help for np.append.

You will find that np.append needs (at least) two arguments, which are:

1. The array to append to, called arr in the documentation and
2. The stuff to append, called values in the documentation.

Here we append a single number:

a = np.append(a, 1.1)
a

array([1.1])

a = np.append(a, 2.2)
a

array([1.1, 2.2])

a = np.append(a, 3.2)
a

array([1.1, 2.2, 3.2])

a = np.append(a, 2.1)
a

array([1.1, 2.2, 3.2, 2.1])

This seems slow and laborious, but we will soon see this can be useful when we want to calculate and store a sequence of values.