Ultimate Visualization with Python

1. Matplotlib Introduction

First, we will discuss plotting applications, Matplotlib library, and its advantages. Afterwards you will create your first simple plot using Matplotlib.

Plotting Applications

Why Use Matplotlib?

Creating a Canvas

Basic Plotting

2. Creating Commonly Used Plots

Now you are ready to create various commonly used in practice plots. Without further ado, let's dive in right now!

3. Plots Customization

Plotting and visualization is not only about creating a plot or several plots, it is also about making them clear, understandable and pleasant to look at. Time to learn plots customization in maplotlib, let's do it!

Adding Title to the Plot

Adding Legend

Axes Customization

Colors and Transparency

Customizing Grid

Subplots

4. More Statistical Plots

Statistics is essential in working with data, hence why it is extremely important to know how to create various statistical plots. Now it's time for us to explore the most common ones.

Histogram

Box Plot

Pie Chart

5. Plotting with Seaborn

Seaborn is another powerful plotting library in Python built on top of matplotlib. Now that you are familiar with matplotlib, it's time to dive into visualization with seaborn.

Why Use Matplotlib?

First of all, what is Matplotlib?

Matplotlib is one of the most used libraries in Python used for data visualization. Despite being comprehensive by allowing the creation of all kinds of static, animated, and interactive visualizations, it is actually quite easy to use. On top of that, matplotlib is open source, which is indeed great.

We believe that starting learning visualization in Python with matplotlib is the best option, since most of the other visualization libraries in Python are built on top of it.

Before diving into matplotlib let's have a look at an example of the plot created with its help:

Looks pretty neat, doesn't it? What if I tell you that this plot can be created with just a few lines of code? Moreover, we can even go as far as making it interactive. That's the power of matplotlib.

Now without further ado let's go to our first task in this course. The majority of matplotlib utilities are located within the pyplot submodule, hence we will use it further in the course.

Task

There are two possible ways to import it, the first one is more common, while the second one is more appropriate according to PEP.

Your task is the following:

Import the pyplot submodule from the matplotlib library with the plt alias without using the from keyword.
Import the pyplot submodule from the matplotlib library with the plt alias using the from keyword.

_{Once you've completed this task, click the button below the code to check your solution.}

Everything was clear?

Section 1. Chapter 2

Course Content

Ultimate Visualization with Python

1. Matplotlib Introduction

Plotting Applications Why Use Matplotlib?Creating a Canvas Basic Plotting

2. Creating Commonly Used Plots

Line Plot Multiple Line Plots Scatter Plot Bar Chart Stacked Bar Charts Grouped Bar Charts

3. Plots Customization

Adding Title to the Plot Adding Legend Axes Customization Colors and Transparency Customizing Grid Subplots

4. More Statistical Plots

Histogram Box Plot Pie Chart

5. Plotting with Seaborn

Seaborn Introduction Countplot Plots Decoration KDE Plot Joint Plot Pair Plot Heatmap

Ultimate Visualization with Python

Why Use Matplotlib?

First of all, what is Matplotlib?

We believe that starting learning visualization in Python with matplotlib is the best option, since most of the other visualization libraries in Python are built on top of it.

Before diving into matplotlib let's have a look at an example of the plot created with its help:

Now without further ado let's go to our first task in this course. The majority of matplotlib utilities are located within the pyplot submodule, hence we will use it further in the course.

Task

There are two possible ways to import it, the first one is more common, while the second one is more appropriate according to PEP.

Your task is the following:

Import the pyplot submodule from the matplotlib library with the plt alias without using the from keyword.
Import the pyplot submodule from the matplotlib library with the plt alias using the from keyword.

_{Once you've completed this task, click the button below the code to check your solution.}

Everything was clear?

Section 1. Chapter 2