R, ggplot - Graphs sharing the same y-axis but with different x-axis scales

Question

Context

I have some datasets/variables and I want to plot them, but I want to do this in a compact way. To do this I want them to share the same y-axis but distinct x-axis and, because of the different distributions, I want one of the x-axis to be log scaled and the other linear scaled.

Example

Suppose I have a long tailed variable (that I want the x-axis to be log-scaled when plotted):

library(PtProcess)
library(ggplot2)

set.seed(1)
lambda <- 1.5
a <- 1
pareto <- rpareto(1000,lambda=lambda,a=a)
x_pareto <- seq(from=min(pareto),to=max(pareto),length=1000)
y_pareto <- 1-ppareto(x_pareto,lambda,a)
df1 <- data.frame(x=x_pareto,cdf=y_pareto)

ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10()

And a normal variable:

set.seed(1)
mean <- 3
norm <- rnorm(1000,mean=mean)
x_norm <- seq(from=min(norm),to=max(norm),length=1000)
y_norm <- pnorm(x_norm,mean=mean)
df2 <- data.frame(x=x_norm,cdf=y_norm)

ggplot(df2,aes(x=x,y=cdf)) + geom_line()

I want to plot them side by side using the same y-axis.

Attempt #1

I can do this with facets, which looks great, but I don't know how to make each x-axis with a different scale ( scale_x_log10() makes both of them log scaled):

df1 <- cbind(df1,"pareto")
colnames(df1)[3] <- 'var'
df2 <- cbind(df2,"norm")
colnames(df2)[3] <- 'var'
df <- rbind(df1,df2)

ggplot(df,aes(x=x,y=cdf)) + geom_line() + 
       facet_wrap(~var,scales="free_x") + scale_x_log10()

Attempt #2

Use grid.arrange , but I don't know how to keep both plot areas with the same aspect ratio:

library(gridExtra)
p1 <- ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10() +
      theme(plot.margin = unit(c(0,0,0,0), "lines"),
            plot.background = element_blank()) +
      ggtitle("pareto")
p2 <- ggplot(df2,aes(x=x,y=cdf)) + geom_line() + 
      theme(axis.text.y = element_blank(), 
            axis.ticks.y = element_blank(), 
            axis.title.y = element_blank(),
            plot.margin = unit(c(0,0,0,0), "lines"),
            plot.background = element_blank()) +
      ggtitle("norm")
grid.arrange(p1,p2,ncol=2)

PS: The number of plots may vary so I'm not looking for an answer specifically for 2 plots

Answer 1

Extending your attempt #2, gtable might be able to help you out. If the margins are the same in the two charts, then the only widths that change in the two plots (I think) are the spaces taken by the y-axis tick mark labels and axis text, which in turn changes the widths of the panels. Using code from here , the spaces taken by the axis text should be the same, thus the widths of the two panel areas should be the same, and thus the aspect ratios should be the same. However, the result (no margin to the right) does not look pretty. So I've added a little margin to the right of p2, then taken away the same amount to the left of p2. Similarly for p1: I've added a little to the left but taken away the same amount to the right.

library(PtProcess)
library(ggplot2)
library(gtable)
library(grid)
library(gridExtra)

set.seed(1)
lambda <- 1.5
a <- 1
pareto <- rpareto(1000,lambda=lambda,a=a)
x_pareto <- seq(from=min(pareto),to=max(pareto),length=1000)
y_pareto <- 1-ppareto(x_pareto,lambda,a)
df1 <- data.frame(x=x_pareto,cdf=y_pareto)

set.seed(1)
mean <- 3
norm <- rnorm(1000,mean=mean)
x_norm <- seq(from=min(norm),to=max(norm),length=1000)
y_norm <- pnorm(x_norm,mean=mean)
df2 <- data.frame(x=x_norm,cdf=y_norm)

p1 <- ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10() +
      theme(plot.margin = unit(c(0,-.5,0,.5), "lines"),
            plot.background = element_blank()) +
      ggtitle("pareto")
p2 <- ggplot(df2,aes(x=x,y=cdf)) + geom_line() + 
      theme(axis.text.y = element_blank(), 
            axis.ticks.y = element_blank(), 
            axis.title.y = element_blank(),
            plot.margin = unit(c(0,1,0,-1), "lines"),
            plot.background = element_blank()) +
      ggtitle("norm")

gt1 <- ggplotGrob(p1)
gt2 <- ggplotGrob(p2)

newWidth = unit.pmax(gt1$widths[2:3], gt2$widths[2:3])

gt1$widths[2:3] = as.list(newWidth)
gt2$widths[2:3] = as.list(newWidth)

grid.arrange(gt1, gt2, ncol=2)

EDIT To add a third plot to the right, we need to take more control over the plotting canvas. One solution is to create a new gtable that contains space for the three plots and an additional space for a right margin. Here, I let the margins in the plots take care of the spacing between the plots.

p1 <- ggplot(df1,aes(x=x,y=cdf)) + geom_line() + scale_x_log10() +
      theme(plot.margin = unit(c(0,-2,0,0), "lines"),
            plot.background = element_blank()) +
      ggtitle("pareto")
p2 <- ggplot(df2,aes(x=x,y=cdf)) + geom_line() + 
      theme(axis.text.y = element_blank(), 
            axis.ticks.y = element_blank(), 
            axis.title.y = element_blank(),
            plot.margin = unit(c(0,-2,0,0), "lines"),
            plot.background = element_blank()) +
      ggtitle("norm")

gt1 <- ggplotGrob(p1)
gt2 <- ggplotGrob(p2)

newWidth = unit.pmax(gt1$widths[2:3], gt2$widths[2:3])

gt1$widths[2:3] = as.list(newWidth)
gt2$widths[2:3] = as.list(newWidth)

 # New gtable with space for the three plots plus a right-hand margin
gt = gtable(widths = unit(c(1, 1, 1, .3), "null"), height = unit(1, "null"))

# Instert gt1, gt2 and gt2 into the new gtable
gt <- gtable_add_grob(gt, gt1, 1, 1)
gt <- gtable_add_grob(gt, gt2, 1, 2)
gt <- gtable_add_grob(gt, gt2, 1, 3)

grid.newpage()
grid.draw(gt)

Answer 2

The accepted answer is exactly what makes people run when comes to plotting using R! This is my solution:

library('grid')
g1 <- ggplot(...)  # however you draw your 1st plot
g2 <- ggplot(...)  # however you draw your 2nd plot
grid.newpage()
grid.draw(cbind(ggplotGrob(g1), ggplotGrob(g2), size = "last"))

This takes care of the y axis (minor and major) guide-lines to align in multiple plots, effortlessly.

Dropping some axis text, unifying the legends, ..., are other tasks that can be taken care of while creating the individual plots, or by using other means provided by grid or gridExtra packages.

Answer 3

The accepted answer looks a little too daunting to me. So I find two ways to get around it with less efforts. Both are based on your Attempt #2 grid.arrange() method.

1. Make plot 1 no y-axis as well

theme(axis.text.y = element_blank(), axis.ticks.y = element_blank(), axis.title.y = element_blank()

So all the plots will be the same. You won't have problems with different aspects ratios. You will need to generate a separate y-axis with R or your favorite image editting app.

2. Fix and respect aspects ratio

Add aspect.ratio = 1 or whatever ratio you desire to theme() of individual plots. Then use respect=TRUE in your grid.arrange()

This way you can keep y-axis in plot1 and still maintains aspects ratio in all plots. Inspired by this answer .

Hope you find these helpful!

Answer 4

I am trying to create a graph for each variable that would then be put together having the same y-axis and ONE label for x-axis.

This code almost works, but the axis are still repeated for each graph.

p1 <- ggplot().....

p2 <- ggplot().....

grid.newpage()
grid.draw(cbind(ggplotGrob(p1), ggplotGrob(p2), size = "last"))

Codeline suggested by @Azim

I am not quite sure if there is an easier way to eliminate the y-axis than to just remove them at the p1 <- ggplot() level. Also I have no idea how to move the x-axis to the middle...

Some visual help:

This is how it is looking now

This is how I want it to look

Thank you for any suggestion!