facet_grid.Rd

% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/facet-grid-.r
\name{facet_grid}
\alias{facet_grid}
\title{Lay out panels in a grid.}
\usage{
facet_grid(facets, margins = FALSE, scales = "fixed", space = "fixed",
  shrink = TRUE, labeller = "label_value", as.table = TRUE,
  switch = NULL, drop = TRUE)
}
\arguments{
\item{facets}{a formula with the rows (of the tabular display) on the LHS
and the columns (of the tabular display) on the RHS; the dot in the
formula is used to indicate there should be no faceting on this dimension
(either row or column). The formula can also be provided as a string
instead of a classical formula object}

\item{margins}{either a logical value or a character
vector. Margins are additional facets which contain all the data
for each of the possible values of the faceting variables. If
\code{FALSE}, no additional facets are included (the
default). If \code{TRUE}, margins are included for all faceting
variables. If specified as a character vector, it is the names of
variables for which margins are to be created.}

\item{scales}{Are scales shared across all facets (the default,
\code{"fixed"}), or do they vary across rows (\code{"free_x"}),
columns (\code{"free_y"}), or both rows and columns (\code{"free"})}

\item{space}{If \code{"fixed"}, the default, all panels have the same size.
 If \code{"free_y"} their height will be proportional to the length of the
 y scale; if \code{"free_x"} their width will be proportional to the
length of the x scale; or if \code{"free"} both height and width will
vary.  This setting has no effect unless the appropriate scales also vary.}

\item{shrink}{If \code{TRUE}, will shrink scales to fit output of
statistics, not raw data. If \code{FALSE}, will be range of raw data
before statistical summary.}

\item{labeller}{A function that takes two arguments (\code{variable} and
\code{value}) and returns a string suitable for display in the facet
strip. See \code{\link{label_value}} for more details and pointers
to other options.}

\item{as.table}{If \code{TRUE}, the default, the facets are laid out like
a table with highest values at the bottom-right. If \code{FALSE}, the
facets are laid out like a plot with the highest value at the top-right.}

\item{switch}{By default, the labels are displayed on the top and
right of the plot. If \code{"x"}, the top labels will be
displayed to the bottom. If \code{"y"}, the right-hand side
labels will be displayed to the left. Can also be set to
\code{"both"}.}

\item{drop}{If \code{TRUE}, the default, all factor levels not used in the
data will automatically be dropped. If \code{FALSE}, all factor levels
will be shown, regardless of whether or not they appear in the data.}
}
\description{
Lay out panels in a grid.
}
\examples{
\donttest{
p <- ggplot(mtcars, aes(mpg, wt)) + geom_point()
# With one variable
p + facet_grid(. ~ cyl)
p + facet_grid(cyl ~ .)

# With two variables
p + facet_grid(vs ~ am)
p + facet_grid(am ~ vs)
p + facet_grid(vs ~ am, margins=TRUE)

# To change plot order of facet grid,
# change the order of variable levels with factor()

set.seed(6809)
diamonds <- diamonds[sample(nrow(diamonds), 1000), ]
diamonds$cut <- factor(diamonds$cut,
         levels = c("Ideal", "Very Good", "Fair", "Good", "Premium"))

# Repeat first example with new order
p <- ggplot(diamonds, aes(carat, ..density..)) +
        geom_histogram(binwidth = 1)
p + facet_grid(. ~ cut)

g <- ggplot(mtcars, aes(mpg, wt)) +
  geom_point()
g + facet_grid(. ~ vs + am)
g + facet_grid(vs + am ~ .)

# You can also use strings, which makes it a little easier
# when writing functions that generate faceting specifications

p + facet_grid("cut ~ .")

# see also ?plotmatrix for the scatterplot matrix

# If there isn't any data for a given combination, that panel
# will be empty

g + facet_grid(cyl ~ vs)

# If you combine a facetted dataset with a dataset that lacks those
# facetting variables, the data will be repeated across the missing
# combinations:

g + facet_grid(vs ~ cyl)

df <- data.frame(mpg = 22, wt = 3)
g + facet_grid(vs ~ cyl) +
  geom_point(data = df, colour = "red", size = 2)

df2 <- data.frame(mpg = c(19, 22), wt = c(2,4), vs = c(0, 1))
g + facet_grid(vs ~ cyl) +
  geom_point(data = df2, colour = "red", size = 2)

df3 <- data.frame(mpg = c(19, 22), wt = c(2,4), vs = c(1, 1))
g + facet_grid(vs ~ cyl) +
  geom_point(data = df3, colour = "red", size = 2)


# You can also choose whether the scales should be constant
# across all panels (the default), or whether they should be allowed
# to vary
mt <- ggplot(mtcars, aes(mpg, wt, colour = factor(cyl))) +
  geom_point()

mt + facet_grid(. ~ cyl, scales = "free")
# If scales and space are free, then the mapping between position
# and values in the data will be the same across all panels
mt + facet_grid(. ~ cyl, scales = "free", space = "free")

mt + facet_grid(vs ~ am, scales = "free")
mt + facet_grid(vs ~ am, scales = "free_x")
mt + facet_grid(vs ~ am, scales = "free_y")
mt + facet_grid(vs ~ am, scales = "free", space = "free")
mt + facet_grid(vs ~ am, scales = "free", space = "free_x")
mt + facet_grid(vs ~ am, scales = "free", space = "free_y")

# You may need to set your own breaks for consistent display:
mt + facet_grid(. ~ cyl, scales = "free_x", space = "free") +
  scale_x_continuous(breaks = seq(10, 36, by = 2))
# Adding scale limits override free scales:
last_plot() + xlim(10, 15)

# Free scales are particularly useful for categorical variables
ggplot(mpg, aes(cty, model)) +
  geom_point() +
  facet_grid(manufacturer ~ ., scales = "free", space = "free")
# particularly when you reorder factor levels
mpg <- within(mpg, {
  model <- reorder(model, cty)
  manufacturer <- reorder(manufacturer, cty)
})
last_plot() \%+\% mpg + theme(strip.text.y = element_text())

# Use as.table to to control direction of horizontal facets, TRUE by default
h <- ggplot(mtcars, aes(x = mpg, y = wt)) +
  geom_point()
h + facet_grid(cyl ~ vs)
h + facet_grid(cyl ~ vs, as.table = FALSE)

# Use labeller to control facet labels, label_value is default
h + facet_grid(cyl ~ vs, labeller = label_both)
# Using label_parsed, see ?plotmath for more options
mtcars$cyl2 <- factor(mtcars$cyl, labels = c("alpha", "beta", "sqrt(x, y)"))
k <- ggplot(mtcars, aes(wt, mpg)) +
  geom_point()
k + facet_grid(. ~ cyl2)
k + facet_grid(. ~ cyl2, labeller = label_parsed)
# For label_bquote the label value is x.
p <- ggplot(mtcars, aes(wt, mpg)) +
  geom_point()
p + facet_grid(. ~ vs, labeller = label_bquote(alpha ^ .(x)))
p + facet_grid(. ~ vs, labeller = label_bquote(.(x) ^ .(x)))

# Margins can be specified by logically (all yes or all no) or by specific
# variables as (character) variable names
mg <- ggplot(mtcars, aes(x = mpg, y = wt)) + geom_point()
mg + facet_grid(vs + am ~ gear)
mg + facet_grid(vs + am ~ gear, margins = TRUE)
mg + facet_grid(vs + am ~ gear, margins = "am")
# when margins are made over "vs", since the facets for "am" vary
# within the values of "vs", the marginal facet for "vs" is also
# a margin over "am".
mg + facet_grid(vs + am ~ gear, margins = "vs")
mg + facet_grid(vs + am ~ gear, margins = "gear")
mg + facet_grid(vs + am ~ gear, margins = c("gear", "am"))

# The facet strips can be displayed near the axes with switch
data <- transform(mtcars,
  am = factor(am, levels = 0:1, c("Automatic", "Manual")),
  gear = factor(gear, levels = 3:5, labels = c("Three", "Four", "Five"))
)
p <- ggplot(data, aes(mpg, disp)) + geom_point()
p + facet_grid(am ~ gear, switch = "both") + theme_light()

# It may be more aesthetic to use a theme without boxes around
# around the strips.
p + facet_grid(am ~ gear + vs, switch = "y") + theme_minimal()
p + facet_grid(am ~ ., switch = "y") +
  theme_gray() \%+replace\% theme(strip.background  = element_blank())
}
}