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Introduction to Data Visualization with ggplot2

4.1+
45 reviews
Beginner

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

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4 Hours14 Videos52 Exercises
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Course Description

The ability to produce meaningful and beautiful data visualizations is an essential part of your skill set as a data scientist. This course, the first R data visualization tutorial in the series, introduces you to the principles of good visualizations and the grammar of graphics plotting concepts implemented in the ggplot2 package. ggplot2 has become the go-to tool for flexible and professional plots in R. Here, we’ll examine the first three essential layers for making a plot - Data, Aesthetics and Geometries. By the end of the course you will be able to make complex exploratory plots.
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In the following Tracks

Certification Available

Data Analyst with R

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Certification Available

Associate Data Scientist in R

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Data Visualization with R

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  1. 1

    Introduction

    Free

    In this chapter we’ll get you into the right frame of mind for developing meaningful visualizations with R. You’ll understand that as a communications tool, visualizations require you to think about your audience first. You’ll also be introduced to the basics of ggplot2 - the 7 different grammatical elements (layers) and aesthetic mappings.

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    Introduction
    50 xp
    Explore and explain
    50 xp
    Drawing your first plot
    100 xp
    Data columns types affect plot types
    100 xp
    The grammar of graphics
    50 xp
    Mapping data columns to aesthetics
    100 xp
    Understanding variables
    50 xp
    ggplot2 layers
    50 xp
    Adding geometries
    100 xp
    Changing one geom or every geom
    100 xp
    Saving plots as variables
    100 xp
  2. 2

    Aesthetics

    Aesthetic mappings are the cornerstone of the grammar of graphics plotting concept. This is where the magic happens - converting continuous and categorical data into visual scales that provide access to a large amount of information in a very short time. In this chapter you’ll understand how to choose the best aesthetic mappings for your data.

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  3. 3

    Geometries

    A plot’s geometry dictates what visual elements will be used. In this chapter, we’ll familiarize you with the geometries used in the three most common plot types you’ll encounter - scatter plots, bar charts and line plots. We’ll look at a variety of different ways to construct these plots.

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  4. 4

    Themes

    In this chapter, we’ll explore how understanding the structure of your data makes data visualization much easier. Plus, it’s time to make our plots pretty. This is the last step in the data viz process. The Themes layer will enable you to make publication quality plots directly in R. In the next course we'll look at some extra layers to add more variables to your plots.

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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 R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track

Data Visualization with R

Go To Track

Datasets

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Collaborators

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Jonathan Ng
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Shon Inouye
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Richie Cotton
Rick Scavetta HeadshotRick Scavetta

Rick Scavetta is a co-founder of Scavetta Academy.

Rick Scavetta is a biologist, workshop trainer, freelance data scientist and co-founder of Scavetta Academy, a company dedicated to helping scientists better understand and visualize their data. Rick's practical, hands-on exposure to a wide variety of datasets has informed him of the many problems scientists face when trying to visualize their data.
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*4.1
from 45 reviews
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  • Igor N.
    10 months

    I've learned a couple new things that weren't mentioned in my classes.

  • James K.
    12 months

    Was a very engaging and practical course.

  • Alejandra M.
    about 1 year

    very informative

  • David P.
    about 1 year

    Wunderbar

  • Mohsen G.
    over 1 year

    I find it exhaustive and well explained xith many exercices

"I've learned a couple new things that weren't mentioned in my classes."

Igor N.

"Was a very engaging and practical course."

James K.

"very informative"

Alejandra M.

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