ggpairs - A ggplot2 generalized pairs plot

Description

Make a matrix of plots with a given data set

Usage

ggpairs(data, mapping = NULL, columns = 1:ncol(data), title = NULL,
  upper = list(continuous = "cor", combo = "box_no_facet", discrete =
  "facetbar", na = "na"), lower = list(continuous = "points", combo =
  "facethist", discrete = "facetbar", na = "na"), diag = list(continuous =
  "densityDiag", discrete = "barDiag", na = "naDiag"), params = NULL, ...,
  xlab = NULL, ylab = NULL, axisLabels = c("show", "internal", "none"),
  columnLabels = colnames(data[columns]), labeller = "label_value",
  switch = NULL, showStrips = NULL, legend = NULL,
  cardinality_threshold = 15, legends = stop("deprecated"))

Arguments

Details

upper and lower are lists that may contain the variables 'continuous', 'combo', 'discrete', and 'na'. Each element of the list may be a function or a string. If a string is supplied, it must implement one of the following options:

continuous

exactly one of ('points', 'smooth', 'smooth_loess', 'density', 'cor', 'blank'). This option is used for continuous X and Y data.

combo

exactly one of ('box', 'box_no_facet', 'dot', 'dot_no_facet', 'facethist', 'facetdensity', 'denstrip', 'blank'). This option is used for either continuous X and categorical Y data or categorical X and continuous Y data.

discrete

exactly one of ('facetbar', 'ratio', 'blank'). This option is used for categorical X and Y data.

na

exactly one of ('na', 'blank'). This option is used when all X data is NA, all Y data is NA, or either all X or Y data is NA.

diag is a list that may only contain the variables 'continuous', 'discrete', and 'na'. Each element of the diag list is a string implementing the following options:

continuous

exactly one of ('densityDiag', 'barDiag', 'blankDiag'). This option is used for continuous X data.

discrete

exactly one of ('barDiag', 'blankDiag'). This option is used for categorical X and Y data.

na

exactly one of ('naDiag', 'blankDiag'). This option is used when all X data is NA.

If 'blank' is ever chosen as an option, then ggpairs will produce an empty plot.

If a function is supplied as an option to upper, lower, or diag, it should implement the function api of function(data, mapping, ...){#make ggplot2 plot}. If a specific function needs its parameters set, wrap(fn, param1 = val1, param2 = val2) the function with its parameters.

Value

ggmatrix object that if called, will print

Author(s)

Barret Schloerke schloerke@gmail.com, Jason Crowley crowley.jason.s@gmail.com, Di Cook dicook@iastate.edu, Heike Hofmann hofmann@iastate.edu, Hadley Wickham h.wickham@gmail.com

References

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.

See Also

wrap v1_ggmatrix_theme

Examples

 # small function to display plots only if it's interactive
 p_ <- GGally::print_if_interactive


## Quick example, with and without colour
data(flea)
ggpairs(flea, columns = 2:4)
pm <- ggpairs(flea, columns = 2:4, ggplot2::aes(colour=species))
p_(pm)
# Note: colour should be categorical, else you will need to reset
# the upper triangle to use points instead of trying to compute corr

data(tips, package = "reshape")
pm <- ggpairs(tips[, 1:3])
p_(pm)
pm <- ggpairs(tips, 1:3, columnLabels = c("Total Bill", "Tip", "Sex"))
p_(pm)
pm <- ggpairs(tips, upper = "blank")
p_(pm)

## Plot Types
# Change default plot behavior
pm <- ggpairs(
  tips[, c(1, 3, 4, 2)],
  upper = list(continuous = "density", combo = "box_no_facet"),
  lower = list(continuous = "points", combo = "dot_no_facet")
)
p_(pm)
# Supply Raw Functions (may be user defined functions!)
pm <- ggpairs(
  tips[, c(1, 3, 4, 2)],
  upper = list(continuous = ggally_density, combo = ggally_box_no_facet),
  lower = list(continuous = ggally_points, combo = ggally_dot_no_facet)
)
p_(pm)

# Use sample of the diamonds data
data(diamonds, package="ggplot2")
diamonds.samp <- diamonds[sample(1:dim(diamonds)[1], 1000), ]

# Different aesthetics for different plot sections and plot types
pm <- ggpairs(
 diamonds.samp[, 1:5],
 mapping = ggplot2::aes(color = cut),
 upper = list(continuous = wrap("density", alpha = 0.5), combo = "box_no_facet"),
 lower = list(continuous = wrap("points", alpha = 0.3), combo = wrap("dot_no_facet", alpha = 0.4)),
 title = "Diamonds"
)
p_(pm)

## Axis Label Variations
# Only Variable Labels on the diagonal (no axis labels)
pm <- ggpairs(tips[, 1:3], axisLabels="internal")
p_(pm)
# Only Variable Labels on the outside (no axis labels)
pm <- ggpairs(tips[, 1:3], axisLabels="none")
p_(pm)

## Facet Label Variations
#  Default:
df_x <- rnorm(100)
df_y <- df_x + rnorm(100, 0, 0.1)
df <- data.frame(x = df_x, y = df_y, c = sqrt(df_x^2 + df_y^2))
pm <- ggpairs(
  df,
  columnLabels = c("alpha[foo]", "alpha[bar]", "sqrt(alpha[foo]^2 + alpha[bar]^2)")
)
p_(pm)
#  Parsed labels:
pm <- ggpairs(
  df,
  columnLabels = c("alpha[foo]", "alpha[bar]", "sqrt(alpha[foo]^2 + alpha[bar]^2)"),
  labeller = "label_parsed"
)
p_(pm)

## Plot Insertion Example
custom_car <- ggpairs(mtcars[, c("mpg", "wt", "cyl")], upper = "blank", title = "Custom Example")
# ggplot example taken from example(geom_text)
  plot <- ggplot2::ggplot(mtcars, ggplot2::aes(x=wt, y=mpg, label=rownames(mtcars)))
  plot <- plot +
    ggplot2::geom_text(ggplot2::aes(colour=factor(cyl)), size = 3) +
    ggplot2::scale_colour_discrete(l=40)
custom_car[1, 2] <- plot
personal_plot <- ggally_text(
  "ggpairs allows you\nto put in your\nown plot.\nLike that one.\n <---"
)
custom_car[1, 3] <- personal_plot
p_(custom_car)

## Remove binwidth warning from ggplot2
# displays warning about picking a better binwidth
pm <- ggpairs(tips, 2:3)
p_(pm)
# no warning displayed
pm <- ggpairs(tips, 2:3, lower = list(combo = wrap("facethist", binwidth = 0.5)))
p_(pm)
# no warning displayed with user supplied function
pm <- ggpairs(tips, 2:3, lower = list(combo = wrap(ggally_facethist, binwidth = 0.5)))
p_(pm)