Who Should Take the Course?

Get introduced to the ggplot2 data visualization course and know who can benefit from this course.

Why learn the ggplot2 package?

  • This course will benefit you if you are a data scientist or a data analyst who wants to develop data visualizations regularly.
  • If you are a data science enthusiast who wants to learn how to quickly and efficiently generate visualizations, this course about the ggplot2 package is undoubtedly for you.
  • Additionally, for an R beginner or anyone looking for a single comprehensive course covering all of the fundamental concepts of the ggplot2 package, this course is good for you, too.

However, this course is not intended for individuals from the business domain, as it includes R programming to generate data visualizations. These users might usually prefer learning no-code/low-code tools such as Power BI, Tableau, Looker, and many more, specially targeted for business intelligence purposes.

Recommended prerequisites

To understand each concept discussed in this course, the learner needs to have:

  • A basic understanding of R programming language.
  • Some familiarity with commonly used techniques for data visualization, such as bar graphs, histograms, scatter plots, and so on.

Don’t worry! Even if you are a complete novice in R, the initial lessons in this course will help you ease into it.

Roadmap to learning the ggplot2 package

The roadmap to this course is simple and convenient to follow. In the first two chapters, you’ll get acquainted with the importance of data visualization, the basics of the ggplot2 package, and the theory for the grammar of graphics. From chapter 3 onward, you’ll begin working on code-based examples. In Chapter 3, you’ll understand how to import datasets in R before using the ggplot2 package and follow step-by-step instructions to build common data visualizations such as bar, line, pie charts, etc. In chapter 4, you’ll learn to create advanced plots in the ggplot2 package, such as correlogram, heat map, violin plot, and many more. The remaining chapters will take you through the customization of these plots, and finally, you’ll create your first interactive plot in the ggplot2 package using Plotly.

What will you learn?

On the successful completion of this course, you’ll:

  • Understand the basics and importance of data visualization.
  • Be familiar with the concept of the grammar of graphics and its elements.
  • Know about the ggplot2 package and how to use different datasets with it.
  • Be aware of aesthetics and annotation in ggplot2.
  • Plot basic charts (e.g., bar, line, scatter) and advanced charts (e.g., violin, lollipop, heatmap).
  • Plot individual as well as the panel of plots.
  • Know how to add titles and subtitles to a plot and adjust the border color and width.

A glimpse of some data visualizations that can be generated using the ggplot2 package:

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Examples of data visualizations with the ggplot2 package
Examples of data visualizations with the ggplot2 package

Key takeaway skills from the course

Based on the course learnings, you can easily:

  • Apply different built-in themes to a plot.
  • Customize the ggplot2 package themes using different elements, the style, and the appearance of the plots.
  • Customize the grid and legends of a plot.
  • Bring interactivity to the ggplot2 package visualizations using additional R packages.

In summary, developing adequate skills in common data visualization techniques will help you to accrue the benefits of decision-making based on data. When you effectively visualize organizational data, it serves as a first step to leveraging data through data analytics. As a data science professional, using these skills, you can likely contribute to better business growth and cost optimization for your organization.

So, welcome onboard this course for building the data visualization skills and knowledge essential to create presentation-ready charts for your next project using the ggplot2 package in R. Let’s begin the journey to learning the ggplot2 package.