Course Content

Visualization in Python with matplotlib

Welcome to the course! In this course, we will learn the `matplotlib`

library, probably, one of the most popular visualization tools for Python. Within the course, we will focus on `pyplot`

- state-based interface to `matplotlib`

.

Common practice is using the

`plt`

alias for`matplotlib.pyplot`

. This is not compulsory, but widely used by Python community, so I recommend you to follow this rule.

The basic concept of building plots in `matplotlib`

is using two objects: **Figure** as a space for building your graph and **Axes** - an area where points can be specified (usually in terms of x-y coordinates, but also in a 3D plot, for example, and so on).

To create both **Figure** and **Axes** objects, you can use the `.subplots()`

function from `matplotlib.pyplot`

using multiple assignment (we need to create two variables: for `Figure`

and `Axes`

objects). That's why using an alias is a good practice. Finally, after assigning `Figure`

and `Axes`

objects to certain variables, we can initialize an empty plot by applying the `.plot()`

function to the `Axes`

object. Finally, we use `plt.show()`

to display the plot.

Section 1.

Chapter 1