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  3. Intermediate Data Visualization with ggplot2
  • 1

    Statistics

    Free

    A picture paints a thousand words, which is why R ggplot2 is such a powerful tool for graphical data analysis. In this chapter, you’ll progress from simply plotting data to applying a variety of statistical methods. These include a variety of linear models, descriptive and inferential statistics (mean, standard deviation and confidence intervals) and custom functions.

  • 2

    Coordinates

    The Coordinates layers offer specific and very useful tools for efficiently and accurately communicating data. Here we’ll look at the various ways of effectively using these layers, so you can clearly visualize lognormal datasets, variables with units, and periodic data.

  • 3

    Facets

    Facets let you split plots into multiple panes, each displaying subsets of the dataset. Here you'll learn how to wrap facets and arrange them in a grid, as well as providing custom labeling.

  • 4

    Best Practices

    Now that you have the technical skills to make great visualizations, it’s important that you make them as meaningful as possible. In this chapter, you’ll review three plot types that are commonly discouraged in the data viz community: heat maps, pie charts, and dynamite plots. You’ll learn the pitfalls with these plots and how to avoid making these mistakes yourself.

Initializing

Exercise

Zooming In

In the video, you saw different ways of using the coordinates layer to zoom in. In this exercise, we'll compare zooming by changing scales and by changing coordinates.

The big difference is that the scale functions change the underlying dataset, which affects calculations made by computed geoms (like histograms or smooth trend lines), whereas coordinate functions make no changes to the dataset.

A scatter plot using mtcars with a LOESS smoothed trend line is provided. Take a look at this before updating it.

Instructions 1/2

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  • 1

    Update the plot by adding (+) a continuous x scale with limits from 3 to 6. Spoiler: this will cause a problem!

  • 2

    Update the plot by adding a Cartesian coordinate system with x limits, xlim, from 3 to 6.