Intermediate Interactive Data Visualization with plotly in R

Learn to create animated graphics and linked views entirely in R with plotly.
Start Course for Free
4 Hours15 Videos54 Exercises2,639 Learners
4400 XP

Create Your Free Account

GoogleLinkedInFacebook
or
By continuing you accept the Terms of Use and Privacy Policy. You also accept that you are aware that your data will be stored outside of the EU and that you are above the age of 16.

Loved by learners at thousands of companies


Course Description

The plotly package enables the construction of interactive and animated graphics entirely within R. This goes beyond basic interactivity such as panning, zooming, and tooltips. In this course, you will extend your understanding of plotly to create animated and linked interactive graphics, which will enable you to communicate multivariate stories quickly and effectively. Along the way, you will review the basics of plotly, learn how to wrangle your data in new ways to facilitate cumulative animations, and learn how to add filters to your graphics without using Shiny.

  1. 1

    Introduction and review of plotly

    Free
    A review of key plotly commands. You will review how to create multiple plot types in plotly and how to polish your charts. Additionally, you will create static versions of the bubble and line charts that you will animate in the next chapter.
    Play Chapter Now
  2. 2

    Animating graphics

    In this chapter, you will learn how to implement keyframe animation in plotly. You will explore how to create animations, such as Hans Rosling's bubble charts, as well as cumulative animations, such as an animation of a stock's valuation over time.
    Play Chapter Now
  3. 3

    Linking graphics

    When you are exploring unexpected structure in your graphics, it's useful to have selections made on one chart update the other. For example, if you are exploring clusters observed on a scatterplot, it is useful to have the selected cluster update some chart of group membership, such as a jittered scatterplot or sets of bar charts. In this chapter, you will learn how to link your plotly charts to enable linked brushing. Along the way, you will also learn how to add dropdown menus, checkboxes, and sliders to your plotly charts, without the need for Shiny.
    Play Chapter Now
  4. 4

    Case Study: Space launches

    In the final chapter, you will use your expanded plotly toolkit to explore orbital space launches between 1957 and 2018. Along the way, you'll learn how to wrangle data to enable cumulative animations without common starting points, and hone your understanding of the crosstalk package.
    Play Chapter Now
In the following tracks
Interactive Data Visualization
Collaborators
David CamposChester Ismay
Adam Loy Headshot

Adam Loy

Assistant Professor of Statistics at Carleton College
Adam is an assistant professor of statistics at Carleton College where he teaches courses in statistics in data science. His research interests lie in statistical graphics and computing, R development, and statistics/data science education. Find out more on Adam's webpage.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA