R – Add legend to ggplot histogram with overlayed density plots

Any ggplots side-by-side (or n plots on a grid)

The function grid.arrange() in the gridExtra package will combine multiple plots; this is how you put two side by side.

require(gridExtra)
plot1 <- qplot(1)
plot2 <- qplot(1)
grid.arrange(plot1, plot2, ncol=2)

This is useful when the two plots are not based on the same data, for example if you want to plot different variables without using reshape().

This will plot the output as a side effect. To print the side effect to a file, specify a device driver (such as pdf, png, etc), e.g.

pdf("foo.pdf")
grid.arrange(plot1, plot2)
dev.off()

or, use arrangeGrob() in combination with ggsave(),

ggsave("foo.pdf", arrangeGrob(plot1, plot2))

This is the equivalent of making two distinct plots using par(mfrow = c(1,2)). This not only saves time arranging data, it is necessary when you want two dissimilar plots.

Appendix: Using Facets

Facets are helpful for making similar plots for different groups. This is pointed out below in many answers below, but I want to highlight this approach with examples equivalent to the above plots.

mydata <- data.frame(myGroup = c('a', 'b'), myX = c(1,1))

qplot(data = mydata, 
    x = myX, 
    facets = ~myGroup)

ggplot(data = mydata) + 
    geom_bar(aes(myX)) + 
    facet_wrap(~myGroup)

Update

the plot_grid function in the cowplot is worth checking out as an alternative to grid.arrange. See the answer by @claus-wilke below and this vignette for an equivalent approach; but the function allows finer controls on plot location and size, based on this vignette.

You can easily add a second legend by adding the line:

ax2.legend(loc=0)

You'll get this:

But if you want all labels on one legend then you should do something like this:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
rc('mathtext', default='regular')

time = np.arange(10)
temp = np.random.random(10)*30
Swdown = np.random.random(10)*100-10
Rn = np.random.random(10)*100-10

fig = plt.figure()
ax = fig.add_subplot(111)

lns1 = ax.plot(time, Swdown, '-', label = 'Swdown')
lns2 = ax.plot(time, Rn, '-', label = 'Rn')
ax2 = ax.twinx()
lns3 = ax2.plot(time, temp, '-r', label = 'temp')

# added these three lines
lns = lns1+lns2+lns3
labs = [l.get_label() for l in lns]
ax.legend(lns, labs, loc=0)

ax.grid()
ax.set_xlabel("Time (h)")
ax.set_ylabel(r"Radiation ($MJ\,m^{-2}\,d^{-1}$)")
ax2.set_ylabel(r"Temperature ($^\circ$C)")
ax2.set_ylim(0, 35)
ax.set_ylim(-20,100)
plt.show()

Which will give you this: