achieving pairwise combinations using ggplot2

Question

I'm trying to do all pairwise scatterplots of a single variable using ggplot2. Something similar to the default pairs(), but I'd like to manipulate the faceting and coloring with ggplot2. here is a failing example of my current attempt in ggplot2

iris_melt = melt(iris)
ggplot(iris_melt, aes(value,value)) + geom_point() + facet_wrap(variable~variable)

What I would like is a plot of:

Sepal.Length vs Sepal.Width
Sepal.Length vs Petal.Length
etc.

I know ggpairs from GGally would do the trick in this situation, however I'd like to do custom faceting and I don't see why I'd need to 'unmelt' the data instead of keeping it tidy

I think melting the data frame is not the right choice while you should try with something like `ggpairs` — adaien, Mar 29 '16 at 15:20
For an interactive analysis `library(rggobi); ggobi(iris)` could be an interesting alternative. — RHertel, Mar 29 '16 at 16:28

score 2 · Answer 1 · answered Mar 29 '16 at 15:07

2

There is already a built-in function

 library(GGally)
 ggpairs(iris)

answered Mar 29 '16 at 15:07

adaien

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I guess I'm trying to teach myself ggplot, and I thought that a 'tidy', or melted data frame was always the way to go. with ggpairs i need to 'unmelt' the data. – kmace Mar 29 '16 at 15:09
I understand that but this approach is suggested by the package author as well. Melting the data frame is sometimes very useful with `ggplot2` but this is not the case – adaien Mar 29 '16 at 15:29

score 2 · Answer 2 · answered Apr 20 '18 at 16:38

You can supply a custom function to ggpairs which allows you to control all the usual ggplot parameters

df <- read.table("test.txt")

upperfun <- function(data,mapping){
  ggplot(data = data, mapping = mapping)+
    geom_density2d()+
    scale_x_continuous(limits = c(-1.5,1.5))+
    scale_y_continuous(limits = c(-1.5,1.5))
}   

lowerfun <- function(data,mapping){
  ggplot(data = data, mapping = mapping)+
    geom_point()+
    scale_x_continuous(limits = c(-1.5,1.5))+
    scale_y_continuous(limits = c(-1.5,1.5))
}  


ggpairs(df,upper = list(continuous = wrap(upperfun)),
        lower = list(continuous = wrap(lowerfun)))

See this question for the data and context

score -1 · Answer 3 · edited May 23 '17 at 11:50

-1

Another post on stack overflow suggests that you enumerate the data, making an additional column for each comparison:

Faceting plots by combinations of columns in ggplot2

This gets what I want, but its definitely not elegant when doing pairwise combinations between multiple columns.

edited May 23 '17 at 11:50

Community

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answered Mar 29 '16 at 15:25

kmace

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achieving pairwise combinations using ggplot2

3 Answers3