ggpairs
is a special form of a ggmatrix
that produces a pairwise comparison of multivariate data. By default, ggpairs
provides two different comparisons of each pair of columns and displays either the density or count of the respective variable along the diagonal. With different parameter settings, the diagonal can be replaced with the axis values and variable labels.
There are many hidden features within ggpairs. Please take a look at the examples below to get the most out of ggpairs.
The columns
displayed default to all columns of the provided data
. To subset to only a few columns, use the columns
parameter.
data(tips, package = "reshape")
pm <- ggpairs(tips)
pm
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## too many plots for this example.
## reduce the columns being displayed
## these two lines of code produce the same plot matrix
pm <- ggpairs(tips, columns = c(1, 6, 2))
pm <- ggpairs(tips, columns = c("total_bill", "time", "tip"), columnLabels = c("Total Bill", "Time of Day", "Tip"))
pm
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Aesthetics can be applied to every subplot with the mapping
parameter.
library(ggplot2)
## [1] TRUE
pm <- ggpairs(tips, mapping = aes(color = sex), columns = c("total_bill", "time", "tip"))
pm
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Since the plots are default plots (or are helper functions from GGally), the aesthetic color is altered to be appropriate. Looking at the example above, 'tip' vs 'total_bill' (pm[3,1]) needs the color
aesthetic, while 'time' vs 'total_bill' needs the fill
aesthetic. If custom functions are supplied, no aesthetic alterations will be done.
There are three major sections of the pairwise matrix: lower
, upper
, and diag
. The lower
and upper
may contain three plot types: continuous
, combo
, and discrete
. The 'diag' only contains either continuous
or discrete
.
continuous
: both X and Y are continuous variablescombo
: one X and Y variable is discrete while the other is continuousdiscrete
: both X and Y are discrete variablesTo make adjustments to each section, a list of information may be supplied. The list can be comprised of the following elements:
continuous
:
ggally_NAME
function, or a custom functionupper$continuous
and lower$continuous
character strings: 'points', 'smooth', 'density', 'cor', 'blank'diag$continuous
character strings: 'densityDiag', 'barDiag', 'blankDiag'combo
:
ggally_NAME
function, or a custom function. (not applicable for a diag
list)upper$combo
and lower$combo
character strings: 'box', 'dot', 'facethist', 'facetdensity', 'denstrip', 'blank'discrete
:
ggally_NAME
function, or a custom functionupper$discrete
and lower$discrete
character strings: 'ratio', 'facetbar', 'blank'diag$discrete
character strings: 'barDiag', 'blankDiag'mapping
: if mapping is provided, only the section's mapping will be overwrittenlibrary(ggplot2)
## [1] TRUE
pm <- ggpairs(
tips, columns = c("total_bill", "time", "tip"),
lower = list(
continuous = "smooth",
combo = "facetdensity",
mapping = aes(color = time)
)
)
pm
A section list may be set to the character string "blank"
or NULL
if the section should be skipped when printed.
pm <- ggpairs(
tips, columns = c("total_bill", "time", "tip"),
upper = "blank",
diag = NULL
)
pm
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
The ggally_NAME
functions do not provide all graphical options. Instead of supplying a character string to a continuous
, combo
, or discrete
element within upper
, lower
, or diag
, a custom function may be given.
The custom function should follow the api of
custom_function <- function(data, mapping, ...){
# produce ggplot2 object here
}
There is no requirement to what happens within the function, as long as a ggplot2 object is returned.
my_bin <- function(data, mapping, ..., low = "#132B43", high = "#56B1F7") {
ggplot(data = data, mapping = mapping) +
geom_bin2d(...) +
scale_fill_gradient(low = low, high = high)
}
pm <- ggpairs(
tips, columns = c("total_bill", "time", "tip"),
lower = list(
continuous = my_bin
)
)
pm
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
The examples above use default parameters to each of the subplots. One of the immediate parameters to be set it binwidth
. This parameters is only needed in the lower, combination plots where one variable is continuous while the other variable is discrete.
To change the default parameter binwidth
setting, we will wrap
the function. wrap
first parameter should be a character string or a custom function. The remaining parameters supplied to wrap will be supplied to the function at run time.
pm <- ggpairs(
tips, columns = c("total_bill", "time", "tip"),
lower = list(
combo = wrap("facethist", binwidth = 1),
continuous = wrap(my_bin, binwidth = c(5, 0.5), high = "red")
)
)
pm
To get finer control over parameters, please look into custom functions.
Please look at the vignette for ggmatrix on plot matrix manipulations.
Small ggpairs example:
pm <- ggpairs(tips, columns = c("total_bill", "time", "tip"))
# retrieve the third row, first column plot
p <- pm[3,1]
p <- p + aes(color = time)
p
pm[3,1] <- p
pm
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Please look at the vignette for ggmatrix on plot matrix manipulations.
Small ggpairs example:
pmBW <- pm + theme_bw()
pmBW
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
John W Emerson, Walton A Green, Barret Schloerke, Jason Crowley, Dianne Cook, Heike Hofmann, Hadley Wickham. The Generalized Pairs Plot. Journal of Computational and Graphical Statistics, vol. 22, no. 1, pp. 79-91, 2012.