Subplot axis labels code#

Subplot axis labels code#

Here’s the code without all the discussion. Patchwork] = patchwork] + theme( = element_blank(), patchwork = elevplot + gradplot + slpplot Margins can be controlled the same was as in the egg example above. The result has nice spacing for a single, shared y axis. (Of course, I also could have built the plots how I wanted them in the first place. If we give the resulting combined plot a name, we can remove the titles from the last two subplots using double-bracket indexing. Here’s an example, combining my three original plots. In patchwork the + operator is used to add plots together. It has nice vignettes here to help you get started. The patchwork package is another one that is great for combining plots, and is now on CRAN (as of December 2019) 🎉. This can be done separately per axis in the development version of ggplot2, and will be included in version 3.2.0. In this case we’d want to change the axis ticks length to 0 via theme() elements. We might want to add a right y axis to the right-most plot. It’d make sense to build these plots outside of ggarrange() and then add the tags and combine them instead of nesting everything like I did here, since the code is now a little hard to follow. However, we can get tricky with egg::tag_facet() if we add a facet strip to each of the individual plots. You’ll see there is a labels argument in ggarrange() documentation, but it didn’t work well for me out of the box with only one plot with a y axis. I’ll set the spacing for right margin of the first plot, both left and right margins of the second, and the left margin of the third. We can bring panes closer by removing some of the space around the plot margins with the plot.margin in theme(). The panel spacing is automagically the same here after I remove the y axis elements, and things look pretty nice right out of the box. The ggarrange() function has an nrow argument so I can keep the plots in a single row. elevplot = ggplot(dat, aes(x = elev, y = resp) ) + The function in this package for combining plots is called ggarrange(). Package egg is another nice alternative for combining plots into a small multiples plot. The cowplot package author points us to package egg for this in this Stack Overflow answer.

It turns out that cowplot isn’t really made for plots with a single shared axis. cowplot::plot_grid(elevplot,īut, unfortunately, this puts the axis space back between the plots to make them all the same width. To have all the plots the same width I need to align them vertically with align = 'v'. This makes panels different sizes, though, which isn’t ideal. I’ll remake the combined plot, this time removing the y axis elements from all but the first plot. cowplot::plot_grid(elevplot,īut we want a single shared y axis, not a separate y axis on each plot. The labels argument puts separate labels on each panel for captioning. To make a single row of plots I use nrow = 1. The function plot_grid() in cowplot is for combining plots. Scale_x_continuous(breaks = seq(0, 35, by = 5) ) Slpplot = ggplot(dat, aes(x = slp, y = resp) ) + Scale_x_continuous(breaks = seq(0, 1, by = 0.2) ) Gradplot = ggplot(dat, aes(x = grad, y = resp) ) + Today I’m going to make the three plots manually. If doing lots of these we’d want to use some sort of loop to make a list of plots as I’ve demonstrated previously. The first step is to make each of the three plots separately. Package cowplot is a really nice package for combining plots, and has lots of bells and whistles along with some pretty thorough vignettes. In that case, it may make more sense to create separate plots and then combine them into a small multiples plot with an add-on package. However, controlling the axis breaks in the individual panels can be complicated, which is something we’d commonly want to do.

Theme(strip.background = element_blank(), ggplot(datlong, aes(x = value, y = resp) ) +įacet_wrap(~variable, scales = 'free_x', strip.position = 'bottom') +

I can use the facet strips to give the appearance of axis labels, as shown in this Stack Overflow answer. ggplot(datlong, aes(x = value, y = resp) ) + The argument scales = 'free_x' allows the x axis scales to differ for each variable but leaves a single y axis. Now I can use facet_wrap() to make a separate scatterplot of resp vs each variable. datlong = gather(dat, key = 'variable', value = 'value', -resp) Since the three variables are currently in separate columns we’ll need to reshape the dataset prior to plotting. One good option when we want to make a similar plot for different groups (in this case, different variables) is to use faceting to make different panels within the same plot.