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

Basic Plotting

Now that you are familiar with the matplotlib architecture you are ready to create your first plot, congratulations! We’ll walk through two possible ways to make a plot:

using scripting approach;
using object-oriented approach (explicit definition instances of Artist objects).

Scipting Approach

With this approach there is no need for you to explicitly create Figure and Axes object (it is done under the hood).

In 2D space, each point has x and y coordinates. To plot it, import the pyplot submodule, use the plt alias, initialize x and y variables, and call the plot() function with x and y as arguments, along with 'o' for the point marker.

Note
The order of the arguments is important!

Finally, we display the plot using plt.show():


              12345
            
import matplotlib.pyplot as plt
x = 5
y = 4
plt.plot(x, y, 'o')
plt.show()

Object-oriented Approach

The only difference here is that instead of directly calling the plot() function, we create a Figure and Axes object using the subplots() functions, and then use the .plot() method on the Axes object with the same arguments.


              123456
            
import matplotlib.pyplot as plt
x = 5
y = 4
fig, ax = plt.subplots()
ax.plot(x, y, 'o')
plt.show()

Note
The following two lines are equivalent to plt.plot().

In fact, both options are still equivalent if we use any other plotting function instead of plot().

Further in the course we’ll mostly use a scripting approach, however, it is still important for you to know both of them. Now it’s your turn to plot a point.

Task

Import the pyplot submodule from the matplotlib library with the plt alias.
Assign values 10 and 2 to variables x and y respectively.
Pass x and y as arguments to the plot() function, first x, then y.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 4

Basic Plotting

Now that you are familiar with the matplotlib architecture you are ready to create your first plot, congratulations! We’ll walk through two possible ways to make a plot:

using scripting approach;
using object-oriented approach (explicit definition instances of Artist objects).

Scipting Approach

With this approach there is no need for you to explicitly create Figure and Axes object (it is done under the hood).

Note
The order of the arguments is important!

Finally, we display the plot using plt.show():


              12345
            
import matplotlib.pyplot as plt
x = 5
y = 4
plt.plot(x, y, 'o')
plt.show()

Object-oriented Approach


              123456
            
import matplotlib.pyplot as plt
x = 5
y = 4
fig, ax = plt.subplots()
ax.plot(x, y, 'o')
plt.show()

Note
The following two lines are equivalent to plt.plot().

In fact, both options are still equivalent if we use any other plotting function instead of plot().

Further in the course we’ll mostly use a scripting approach, however, it is still important for you to know both of them. Now it’s your turn to plot a point.

Task

Import the pyplot submodule from the matplotlib library with the plt alias.
Assign values 10 and 2 to variables x and y respectively.
Pass x and y as arguments to the plot() function, first x, then y.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 4

Basic Plotting

Now that you are familiar with the matplotlib architecture you are ready to create your first plot, congratulations! We’ll walk through two possible ways to make a plot:

using scripting approach;
using object-oriented approach (explicit definition instances of Artist objects).

Scipting Approach

With this approach there is no need for you to explicitly create Figure and Axes object (it is done under the hood).

Note
The order of the arguments is important!

Finally, we display the plot using plt.show():


              12345
            
import matplotlib.pyplot as plt
x = 5
y = 4
plt.plot(x, y, 'o')
plt.show()

Object-oriented Approach


              123456
            
import matplotlib.pyplot as plt
x = 5
y = 4
fig, ax = plt.subplots()
ax.plot(x, y, 'o')
plt.show()

Note
The following two lines are equivalent to plt.plot().

In fact, both options are still equivalent if we use any other plotting function instead of plot().

Further in the course we’ll mostly use a scripting approach, however, it is still important for you to know both of them. Now it’s your turn to plot a point.

Task

Import the pyplot submodule from the matplotlib library with the plt alias.
Assign values 10 and 2 to variables x and y respectively.
Pass x and y as arguments to the plot() function, first x, then y.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Now that you are familiar with the matplotlib architecture you are ready to create your first plot, congratulations! We’ll walk through two possible ways to make a plot:

using scripting approach;
using object-oriented approach (explicit definition instances of Artist objects).

Scipting Approach

With this approach there is no need for you to explicitly create Figure and Axes object (it is done under the hood).

Note
The order of the arguments is important!

Finally, we display the plot using plt.show():


              12345
            
import matplotlib.pyplot as plt
x = 5
y = 4
plt.plot(x, y, 'o')
plt.show()

Object-oriented Approach


              123456
            
import matplotlib.pyplot as plt
x = 5
y = 4
fig, ax = plt.subplots()
ax.plot(x, y, 'o')
plt.show()

Note
The following two lines are equivalent to plt.plot().

In fact, both options are still equivalent if we use any other plotting function instead of plot().

Further in the course we’ll mostly use a scripting approach, however, it is still important for you to know both of them. Now it’s your turn to plot a point.

Task

Import the pyplot submodule from the matplotlib library with the plt alias.
Assign values 10 and 2 to variables x and y respectively.
Pass x and y as arguments to the plot() function, first x, then y.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 1. Chapter 4

Switch to desktop for real-world practiceContinue from where you are using one of the options below