Arrays are vital objects in the data analysis scenario. Arrays allow for structured handling of elements that are stacked across rows and columns. The elements of an array are bound by the rule that they should all be of the same data type. For example, the medical records of five patients have been presented as an array as follows:
|
Blood glucose level |
Heart rate |
Cholesterol level |
|
|
Peter Parker |
100 |
65 |
160 |
|
Bruce Wayne |
150 |
82 |
200 |
|
Tony Stark |
90 |
55 |
80 |
|
Barry Allen |
130 |
73 |
220 |
|
Steve Rogers |
190 |
80 |
150 |
It is seen that all 15 elements are of data type int. Arrays could also be composed of strings, floats, or complex numbers. Arrays could be constructed from lists—a widely used and versatile data structure in Python:
array_list = [[100, 65, 160],
[150, 82, 200],
[90, 55, 80],
[130, 73, 220],
[190, 80, 150]...
