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

Seaborn Introduction

Seaborn is a high-level plotting library based on matplotlib. Let’s have a look at its advantages in comparison to matplotlib:

simpler interface;
a wide range of default styles and color palettes;
works well with pandas DataFrame;
a wide range of built-in statistical functions.

Here is an example of a plot created using seaborn with just one line of code:

Apparently, everything you can accomplish using seaborn can be also done with matplotlib, yet it may often take more time and effort.

However, matplotlib being a rather low-level library in comparison, offers more flexibility for your plots, so if you need to create a rather unique plot with a lot of customizations, matplotlib is still the best choice.

Task

Swipe to show code editor

Import the seaborn library with the sns alias.

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 5. Chapter 1

Seaborn Introduction

Seaborn is a high-level plotting library based on matplotlib. Let’s have a look at its advantages in comparison to matplotlib:

simpler interface;
a wide range of default styles and color palettes;
works well with pandas DataFrame;
a wide range of built-in statistical functions.

Here is an example of a plot created using seaborn with just one line of code:

Apparently, everything you can accomplish using seaborn can be also done with matplotlib, yet it may often take more time and effort.

Task

Swipe to show code editor

Import the seaborn library with the sns alias.

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 5. Chapter 1

Seaborn Introduction

Seaborn is a high-level plotting library based on matplotlib. Let’s have a look at its advantages in comparison to matplotlib:

simpler interface;
a wide range of default styles and color palettes;
works well with pandas DataFrame;
a wide range of built-in statistical functions.

Here is an example of a plot created using seaborn with just one line of code:

Apparently, everything you can accomplish using seaborn can be also done with matplotlib, yet it may often take more time and effort.

Task

Swipe to show code editor

Import the seaborn library with the sns alias.

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

Everything was clear?

Thanks for your feedback!

Seaborn is a high-level plotting library based on matplotlib. Let’s have a look at its advantages in comparison to matplotlib:

simpler interface;
a wide range of default styles and color palettes;
works well with pandas DataFrame;
a wide range of built-in statistical functions.

Here is an example of a plot created using seaborn with just one line of code:

Apparently, everything you can accomplish using seaborn can be also done with matplotlib, yet it may often take more time and effort.

Task

Swipe to show code editor

Import the seaborn library with the sns alias.

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

Section 5. Chapter 1

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