Can I tell ggpairs to use log scales?

Can I provide a parameter to the ggpairs function in the GGally p开发者_StackOverflow社区ackage to use log scales for some, not all, variables?

You can't provide the parameter as such (a reason is that the function creating the scatter plots is predefined without scale, see ggally_points), but you can change the scale afterward using getPlot and putPlot. For instance:

custom_scale <- ggpairs(data.frame(x=exp(rnorm(1000)), y=rnorm(1000)),
upper=list(continuous='points'), lower=list(continuous='points'))
subplot <- getPlot(custom_scale, 1, 2) # retrieve the top left chart
subplotNew <- subplot + scale_y_log10() # change the scale to log
subplotNew$type <- 'logcontinuous' # otherwise ggpairs comes back to a fixed scale
subplotNew$subType <- 'logpoints'
custom_scale <- putPlot(custom_fill, subplotNew, 1, 2)

This is essentially the same answer as Jean-Robert but looks much more simple (approachable). I don't know if it is a new feature but it doesn't look like you need to use getPlot or putPlot anymore.

custom_scale[1,2]<-custom_scale[1,2] + scale_y_log10() + scale_x_log10()

Here is a function to apply it across a big matrix. Supply the number of rows in the plot and the name of the plot.

scalelog2<-function(x=2,g){  #for below diagonal
 for (i in 2:x){ 
    for (j in 1:(i-1)) { 
      g[i,(j)]<-g[i,(j)] + scale_x_continuous(trans='log2') +
scale_y_continuous(trans='log2')
                        } } 
 for (i in 1:x){  #for the bottom row 
      g[(x+1),i]<-g[(x+1),i] + scale_y_continuous(trans='log2') 
                       } 
 for (i in 1:x){ #for the diagonal
      g[i,i]<-g[i,i]+ scale_x_continuous(trans='log2')  } 
  return(g) }

It's probably better use a linear scale and log transform variables as appropriate before supplying them to ggpairs because this avoids ambiguity in how the correlation coefficients have been computed (before or after log-transform). This can be easily achieved e.g. like this:

library(tidyverse)

log10_vars <- vars(ends_with(".Length"))             # define variables to be transformed

iris %>%                                             # use standard R example dataframe
  mutate_at(log10_vars, log10) %>%                   # log10 transform selected columns
  rename_at(log10_vars, sprintf, fmt="log10 %s") %>% # rename variables accordingly
  GGally::ggpairs(aes(color=Species))