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Introduction to Data Visualization with Seaborn

4.7+
88 reviews
Beginner

Learn how to create informative and attractive visualizations in Python using the Seaborn library.

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4 Hours14 Videos44 Exercises
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Course Description

Create Your Own Seaborn Plots

Seaborn is a powerful Python library that makes it easy to create informative and attractive data visualizations. This 4-hour course provides an introduction to how you can use Seaborn to create a variety of plots, including scatter plots, count plots, bar plots, and box plots, and how you can customize your visualizations.

Turn Real Datasets into Custom Seaborn Visualizations

You’ll explore this library and create your Seaborn plots based on a variety of real-world data sets, including exploring how air pollution in a city changes through the day and looking at what young people like to do in their free time. This data will give you the opportunity to find out about Seaborn’s advantages first hand, including how you can easily create subplots in a single figure and how to automatically calculate confidence intervals.

Improve Your Data Communication Skills

By the end of this course, you’ll be able to use Seaborn in various situations to explore your data and effectively communicate the results of your data analysis to others. These skills are highly sought-after for data analysts, data scientists, and any other job that may involve creating data visualizations. If you’d like to continue your learning, this course is part of several tracks, including the Data Visualization track, where you can add more libraries and techniques to your skillset.
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In the following Tracks

Certification Available

Data Analyst with Python

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Certification Available

Associate Data Scientist in Python

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Data Visualization with Python

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  1. 1

    Introduction to Seaborn

    Free

    What is Seaborn, and when should you use it? In this chapter, you will find out! Plus, you will learn how to create scatter plots and count plots with both lists of data and pandas DataFrames. You will also be introduced to one of the big advantages of using Seaborn - the ability to easily add a third variable to your plots by using color to represent different subgroups.

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    Introduction to Seaborn
    50 xp
    Making a scatter plot with lists
    100 xp
    Making a count plot with a list
    100 xp
    Using pandas with Seaborn
    50 xp
    "Tidy" vs. "untidy" data
    100 xp
    Making a count plot with a DataFrame
    100 xp
    Adding a third variable with hue
    50 xp
    Hue and scatter plots
    100 xp
    Hue and count plots
    100 xp
  2. 2

    Visualizing Two Quantitative Variables

    In this chapter, you will create and customize plots that visualize the relationship between two quantitative variables. To do this, you will use scatter plots and line plots to explore how the level of air pollution in a city changes over the course of a day and how horsepower relates to fuel efficiency in cars. You will also see another big advantage of using Seaborn - the ability to easily create subplots in a single figure!

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  3. 3

    Visualizing a Categorical and a Quantitative Variable

    Categorical variables are present in nearly every dataset, but they are especially prominent in survey data. In this chapter, you will learn how to create and customize categorical plots such as box plots, bar plots, count plots, and point plots. Along the way, you will explore survey data from young people about their interests, students about their study habits, and adult men about their feelings about masculinity.

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  4. 4

    Customizing Seaborn Plots

    In this final chapter, you will learn how to add informative plot titles and axis labels, which are one of the most important parts of any data visualization! You will also learn how to customize the style of your visualizations in order to more quickly orient your audience to the key takeaways. Then, you will put everything you have learned together for the final exercises of the course!

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For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Certification Available

Data Analyst with Python

Go To Track
Certification Available

Associate Data Scientist in Python

Go To Track

Data Visualization with Python

Go To Track

Datasets

CountriesMileage per gallonStudentsSurvey responses

Collaborators

Collaborator's avatar
Mona Khalil
Collaborator's avatar
Yashas Roy
DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of your browser with video lessons and fun coding challenges and projects.
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Don’t just take our word for it

*4.7
from 88 reviews
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Sort by
  • PASCAL P.
    17 days

    Great learning experience.

  • Samet S.
    3 months

    Clear and very good excercises

  • Joanna R.
    3 months

    I really recommend

  • Aled L.
    3 months

    Good..can see how I'd use these skills, possibly more fun considering there is less coding and data manipulation involved in this area At times I wasn't sure if I had all the info/references to complete a task, quick Google required. Sometimes the AI doesn't want to assist for some reason, add a random extra "X" and it suddenly will help lol

  • Kalpak C.
    3 months

    Beneficial for beginners.

"Great learning experience."

PASCAL P.

"Clear and very good excercises"

Samet S.

"I really recommend"

Joanna R.

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