![]() ![]() First, setup your ggplot code as if you aren’t faceting. Sounds like a lot, but facets can make this very simple. ![]() You want three different plots in the same figure - a timeseries for each of the parameters with different colored symbols for the different sites. You have a ame with four columns: Date, site_no, parameter, and value. Let’s start by considering a set of graphs with a common x axis. You write your ggplot2 code as if you were putting all of the data onto one plot, and then you use one of the faceting functions to specify how to slice up the graph. When you are creating multiple plots and they share axes, you should consider using facet functions from ggplot2 ( facet_grid, facet_wrap). Multiple plots in one figure using ggplot2 and facets However, there are other methods to do this that are optimized for ggplot2 plots. You may have already heard of ways to put multiple R plots into a single figure - specifying mfrow or mfcol arguments to par, split.screen, and layout are all ways to do this. While ggplot2 has many useful features, this post will explore how to create figures with multiple ggplot2 plots. In the Introduction to R class, we have switched to teaching ggplot2 because it works nicely with other tidyverse packages (dplyr, tidyr), and can create interesting and powerful graphics with little code.
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