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Introduction to NumPy
Selecting Elements from a 1-D Array

NumPy allows us to select elements from an array using their indices. Consider the one-dimensional array

``a = np.array([5, 2, 7, 0, 11])``

If we wanted to select the first element in this array, we would call:

``````>>> a
5 ``````

In typical Python fashion, the indices for an array start at `0`. This is known as zero-indexed numbering. In the array above, 5 is known as the zeroth element, `a`. It follows that 2 is the first element, `a`.

We can also select negative indices, which count from opposite end of the array and start at `-1`. This is particularly useful when you want to access the last element or two of an array:

``````>>> a[-1]
11
>>> a[-2]
0``````

If we wanted to select multiple elements in the array, we can define a range, such as `a[1:3]`, which will select all the elements from `a` to `a`, including `a` but excluding `a`.

``````>>> a[1:3]
array([2, 7])``````

Similarly, if we wanted to select all elements before `a` we would use:

``````>>> a[:3]
array([5, 2, 7])``````

We can also use negative indices to select multiple elements. Let’s say we want to select the last 3 elements in an array:

``````>>> a[-3:]
array([7, 0, 11])``````

Notice that when we select multiple elements, we get an array.

### Instructions

1.

Let’s return to our student’s test scores. The following table shows all three test arrays aligned to the names of the students.

test_1 92 94 88 91 87
test_2 79 100 86 93 91
test_3 87 85 72 90 92

Jeremy wants to know what he scored on the second test.

Select the score from the `test_2` array and save it to the variable `jeremy_test_2`.

2.

You want to compare how Manual and Adwoa did on the first test.

Select both of their scores and save them in an array named `manual_adwoa_test_1`.