Interactive Data Visualization with plotly in R

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.

What You’ll Learn

Introduction to plotly

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.

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.

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.

Case Study

In the final chapter, you use your plotly toolkit to explore the results of the 2018 United States midterm elections, learning how to create maps in plotly along the way.