Interactive Data Visualization in R

Have fun creating maps! Interactive Maps with Leaflet In R will show you how to create interactive webmaps from spatial data and tidyverse. This course will show you how to create maps using the IPEDS dataset. It includes data about U.S. universities and colleges. The maps can be customized with labels, popups, and other custom markers. To enhance interactivity, layers can be added. Learn how to create interactive web maps using your data.

Interactive graphics allow you to manipulate plotted data in order to gain more insight. Interactive graphics, for instance, allow you to zoom in on a subset of your data without having to create a new plot. You will learn how to create interactive graphics with plotly and R. Data visualization best practices will be covered, as well as new plot types such scatterplot matrixes or binned scatteredplots.

You can create animated and interactive graphics in R using the plotly package. These will enable you to communicate multivariate stories quickly and efficiently. Learn the basics of plotly, and how to manipulate data to create cumulative animations. You'll also learn how to add filters to your graphics without Shiny.

Now you can tackle larger datasets after mastering ggplot2. This course will show you how to visualize large data using scalable visualization techniques such as faceting. This course will show you how to use Trelliscope, which is part of the trelliscopejs packages. Trelliscope seamlessly integrates with standard R workflows, allowing you to create interactive visualizations that allow you to explore your data deeply. This course will show you how to create interactive exploratory displays using large datasets. This course will help you and your colleagues gain new insights.

Data visualization is an integral part of data analysis. This course will teach you how to use rbokeh, which is a web-based visualization tool that allows interactive plots. You will learn how layers and other options can be used in rbokeh for powerful visualizations that communicate your message and highlight your ideas. We will focus on two important components of data visualization: how do we wrangle the data in the right format, and how to use the visualization tools and charts available from rbokeh.