Interactive Course

Intermediate Interactive Data Visualization with plotly in R

Learn to create animated graphics and linked views entirely in R with plotly.

  • 4 hours
  • 15 Videos
  • 54 Exercises
  • 987 Participants
  • 4,400 XP

Loved by learners at thousands of top companies:

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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.

  2. 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.

  3. 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.

  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.

  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.

  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.

  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.

  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.

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Lloyd's Banking Group

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Harvard Business School

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Decision Science Analytics @ USAA

Adam Loy
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.

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