Lay out panels in a grid.


facet_grid(facets, margins = FALSE, scales = "fixed", space = "fixed", shrink = TRUE, labeller = "label_value", as.table = TRUE, switch = NULL, drop = TRUE)


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
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 FALSE, no additional facets are included (the default). If 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.
Are scales shared across all facets (the default, "fixed"), or do they vary across rows ("free_x"), columns ("free_y"), or both rows and columns ("free")
If "fixed", the default, all panels have the same size. If "free_y" their height will be proportional to the length of the y scale; if "free_x" their width will be proportional to the length of the x scale; or if "free" both height and width will vary. This setting has no effect unless the appropriate scales also vary.
If TRUE, will shrink scales to fit output of statistics, not raw data. If FALSE, will be range of raw data before statistical summary.
A function that takes one data frame of labels and returns a list or data frame of character vectors. Each input column corresponds to one factor. Thus there will be more than one with formulae of the type ~cyl + am. Each output column gets displayed as one separate line in the strip label. This function should inherit from the "labeller" S3 class for compatibility with labeller(). See label_value for more details and pointers to other options.
If TRUE, the default, the facets are laid out like a table with highest values at the bottom-right. If FALSE, the facets are laid out like a plot with the highest value at the top-right.
By default, the labels are displayed on the top and right of the plot. If "x", the top labels will be displayed to the bottom. If "y", the right-hand side labels will be displayed to the left. Can also be set to "both".
If TRUE, the default, all factor levels not used in the data will automatically be dropped. If FALSE, all factor levels will be shown, regardless of whether or not they appear in the data.


Lay out panels in a grid.


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)
Scale for 'x' is already present. Adding another scale for 'x', which will replace the existing scale. Warning message: Removed 26 rows containing missing values (geom_point).

# 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$model <- reorder(mpg$model, mpg$cty) manufacturer <- reorder(mpg$manufacturer, mpg$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())