Figure 1: Basic Scatterplot Created by ggplot2 Package. In Figure 1, you can see the result of the previous R code: A scatterplot of x and y1. Now, let’s assume we want to create a ggplot2 plot of each combination of x and y1, y2, and y3 respectively. In such a scenario, we may want to use a for-loop: for( i in 2: ncol ( data)) { # ggplot

Once the data are in this stacked form, it only requires a simple ggplot () call to produce the plot you wanted with all the extras (one reason why higher-level plotting packages like lattice and ggplot2 are so useful): require (ggplot2) p Combining two different types of plots into one window using ggplot. 3. Convert two ggplots into one. 5. combining plots that share common x axis but not y. 2.
The {ggplot2} package is based on the principles of “The Grammar of Graphics” (hence “gg” in the name of {ggplot2} ), that is, a coherent system for describing and building graphs. The main idea is to design a graphic as a succession of layers. The dataset that contains the variables that we want to represent.
Usage. Themes are a powerful way to customize the non-data components of your plots: i.e. titles, labels, fonts, background, gridlines, and legends. Themes can be used to give plots a consistent customized look. Modify a single plot's theme using theme (); see theme_update () if you want modify the active theme, to affect all subsequent plots.
First, it is necessary to summarize the data. This can be done in a number of ways, as described on this page.In this case, we’ll use the summarySE() function defined on that page, and also at the bottom of this page. jP6e.
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    • how to use ggplot in r