Course Content

# NumPy in a Nutshell

1. Getting Started with NumPy

2. Dimensions in Arrays

3. Indexing and Slicing

4. Important Functions

NumPy in a Nutshell

## Function array()

In fact, there are various functions in **NumPy** for creating arrays. Now, we'll explore one of the most commonly used ones, namely `np.array()`

. Below, you'll find an example of how to use this function:

Let's now determine the type of object that this function creates. We can do this using the well-known function `type()`

.

Note

The

`type()`

function takes an object of any type and returns its type. The argument can indeed be of any type: number, string, list, dictionary, tuple, function, class, module, etc.

We can see the type of the created array is `ndarray`

. But what does that mean?
**ndarray** - This object is a multidimensional homogeneous array with a predetermined number of elements.

Now it's time to practice!

# Task

- You have to create two
**NumPy**arrays. The first one should look like this:`[65, 2, 89, 5, 0, 1]`

and the second one should look like this:`[1, 2, 3]`

. - Display these arrays on the screen. Display the type of these arrays on the screen.

If you encounter any difficulties, refer to the hint; it will likely assist you.

Everything was clear?