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Interactive Data Visualization with plotly in R

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

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4 Hours15 Videos54 Exercises9,146 Learners4600 XPInteractive Data Visualization in R Track

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Course Description

Build Interactive Data Visualizations in plotly

Interactive graphics allow you to manipulate plotted data to gain further insights. As an example, an interactive graphic would allow you to zoom in on a subset of your data without the need to create a new plot. In this course, you will learn how to create and customize interactive graphics in plotly using R.

Get Started Using plotly

You’ll start the course with an introduction to plotly and a view of different plots you can make using this R package, including histograms, bar charts, bivariate graphics, scatterplots, and boxplots. You’ll also learn how to convert a ggplot2 scatterplot into plotly so that you can enhance your graphics and dashboards.

Explore Creating plotly Plots and Dashes

The next two chapters of the course show you how you can customize your graphics to build the perfect dashboard, and even add hover-over information to add detail and depth. Then you’ll move on to advanced charts that visualize complex relationships and larger datasets. By completing this course, you’ll be able to create manual and automated faceting, binned scatterplots, and your first scatter plot matrix (SPLOM).

Create Visualizations with Real-World Data

The final chapter of this course uses your new-found plotly skills to visualize the results of the 2018 US elections. You’ll create the first interactive plotly dash in your portfolio and learn how to create maps using this valuable data visualization tool.
  1. 1

    Introduction to plotly

    Free

    In this chapter, you will receive an introduction to basic graphics with plotly. You will create your first interactive graphics, displaying both univariate and bivariate distributions. Additionally, you will discover how to easily convert ggplot2 graphics to interactive plotly graphics.

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    What is plotly?
    50 xp
    A follow-up on the course intro
    50 xp
    Converting a ggplot2 scatterplot
    100 xp
    Univariate graphics
    50 xp
    Histograms
    100 xp
    Bar charts
    100 xp
    Bivariate graphics
    50 xp
    A first scatterplot
    100 xp
    A first stacked bar chart
    100 xp
    Boxplots
    100 xp
  2. 2

    Styling and customizing your graphics

    In this chapter, you will learn how to customize the appearance of your graphics and use opacity, symbol, and color to clarify your message. You will also learn how to transform axes, label your axes, and customize the hover information of your graphs.

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  3. 3

    Advanced charts

    In this chapter, you move past basic plotly charts to explore more-complex relationships and larger datasets. You will learn how to layer traces, create faceted charts and scatterplot matrices, and create binned scatterplots.

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In the following tracks

Interactive Data Visualization in R

Collaborators

Chester Ismay
David Campos
Shon Inouye
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.
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