"""
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[0]
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[0]. It follows that 2 is the first element, a[1].

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[1] to a[3], including a[1] but excluding a[3].

>>> a[1:3]
array([2, 7])
Similarly, if we wanted to select all elements before a[3] 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.
"""
import numpy as np

test_1 = np.array([92, 94, 88, 91, 87])
test_2 = np.array([79, 100, 86, 93, 91])
test_3 = np.array([87, 85, 72, 90, 92])
"""
Let's return to our student's test scores. The following table shows all three test arrays aligned to the names of the students.

Tanya	Manual	Adwoa	Jeremy	Cody
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.
"""
jeremy_test_2 = test_2[3]

"""
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.
"""
manual_adwoa_test_1 = test_1[1:3]

