Ggplot multipanel figure different legend different sizes
: a list of aesthetics to customize the background of panel labels.For two grouping variables, you can use for example panel.labs = list(sex = c(“Male”, “Female”), rx = c(“Obs”, “Lev”, “Lev2”) ). For example, panel.labs = list(sex = c(“Male”, “Female”)) specifies the labels for the “sex” variable. Panel.labs: a list of one or two character vectors to modify facet label text. If TRUE, create short labels for panels by omitting variable names in other words panels will be labelled only by variable grouping levels. You can also have panels displayed in a other geometries, although they are defined with multiple variables. p <- ggplot(data = mtcars, aes(mpg, wt)) + geom_point() Plot weight versus mpg for each value of vs and carb. Here, the panels are determined by the values of multiple variables. # Warning: invalid factor level, NAs generated Q + geom_point(data = cycl6, color = "red") p <- ggplot(data = mpg, aes(x = displ, y = hwy)) + geom_point() Sometimes we may want to add features to a single facet. Other scales options are "free_x" and "free_xy" Decorating facets The relative sizes between the bins are not so different, though. Visually, it looks like the histograms are about the same and they aren't in actual counts. p + facet_wrap(~color, scales = "free_y") We can get a better plot by letting the y axes vary freely. p <- ggplot(data = diamonds, aes(x = price)) + geom_histogram(binwidth = 1000) Some of the subsets may exhibit extreme bahavior of a variable causing other facets to plot in uncommunicative ways. p <- ggplot(data = mpg, aes(x = displ, y = hwy, color = drv)) + geom_point() We can add an aesthetic for another variable and get one legend. We can control the layout with options to the facet_wrap function.
P <- ggplot(data = mpg, aes(x = displ, y = hwy)) + geom_point() # $ manufacturer: Factor w/ 15 levels "audi","chevrolet".: 1 1 1 1 1 1 1 1 1 1. The panels are calculated in a 1 dimensional ribbon that can be wrapped to multiple rows. Here, a single categorical variable defines subsets of the data. setwd("~/Documents/Computing with Data/13_Facets/") Each panel plot corresponds to a set value of the variable. The faceting is defined by a categorical variable or variables. This is a very useful feature of ggplot2. In some circumstances we want to plot relationships between set variables in multiple subsets of the data with the results appearing as panels in a larger figure. Plotting multiple groups with facets in ggplot2