![]() The ggplot2 package doesn’t have all the answers, but it does provide some tools to make your life a little easier. However, text annotation can be tricky due to the way that R handles fonts. Most plots will not benefit from adding text to every single observation on the plot, but labelling outliers and other important points is very useful. To learn more about how labs() is related to scales in ggplot2, see Section 14.2.Īdding text to a plot is one of the most common forms of annotation. Setting labs(x = "") omits the label but still allocates space setting labs(x = NULL) removes the label and its space. There are two ways to remove the axis label. To assist with this task ggplot2 provides the labs() helper function, which lets you set the various titles using name-value pairs like title = My plot title", x = "X axis" or fill = "fill legend": When customising a plot, it is often useful to modify the titles associated with the plot, axes, and legends. However, to meet the specific needs that users often have when annotating plots, there are some helper functions in ggplot2 itself, and a number of other packages have extended ggplot2 in ways you may find helpful. Because of this, the annotation tools in ggplot2 reuse the same geoms that are used to create other plots. From a practical standpoint, however, metadata is just another form of data. Conceptually, an annotation supplies metadata for the plot: that is, it provides additional information about the data being displayed. When constructing a data visualisation, it is often necessary to make annotations to the data displayed. This chapter should be readable but is currently undergoing final polishing. You are reading the work-in-progress third edition of the ggplot2 book.
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