These functions provide summarised information about built ggplot objects.

summarise_layout(p)

summarise_coord(p)

summarise_layers(p)

## Arguments

p A ggplot_built object.

## Details

There are three types of summary that can be obtained: A summary of the plot layout, a summary of the plot coord, and a summary of plot layers.

## Layout summary

The function summarise_layout() returns a table that provides information about the plot panel(s) in the built plot. The table has the following columns:

panel

A factor indicating the individual plot panels.

row

Row number in the grid of panels.

col

Column number in the grid of panels.

vars

A list of lists. For each panel, the respective list provides the variables and their values that specify the panel.

xmin, xmax

The minimum and maximum values of the variable mapped to the x aesthetic, in transformed coordinates.

ymin, ymax

The minimum and maximum values of the variable mapped to the y aesthetic, in transformed coordinates.

xscale

The scale object applied to the x aesthetic.

yscale

The scale object applied to the y aesthetic.

Importantly, the values for xmin, xmax, ymin, ymax, xscale, and yscale are determined by the variables that are mapped to x and y in the aes() call. So even if a coord changes how x and y are shown in the final plot (as is the case for coord_flip() or coord_polar()), these changes have no effect on the results returned by summarise_plot().

## Coord summary

The function summarise_coord() returns information about the log base for coordinates that are log-transformed in coord_trans(), and it also indicates whether the coord has flipped the x and y axes.

## Layer summary

The function summarise_layers() returns a table with a single column, mapping, which contains information about aesthetic mapping for each layer.

## Examples

p <- ggplot(mpg, aes(displ, hwy)) + geom_point() + facet_wrap(~class)
b <- ggplot_build(p)

summarise_layout(b)#> # A tibble: 7 x 10
#>   panel   row   col vars     xmin  xmax  ymin  ymax xscale        yscale
#>   <fct> <int> <int> <list>  <dbl> <dbl> <dbl> <dbl> <list>        <list>
#> 1 1         1     1 <list …  1.33  7.27  10.4  45.6 <S3: ScaleCo… <S3: ScaleCo…
#> 2 2         1     2 <list …  1.33  7.27  10.4  45.6 <S3: ScaleCo… <S3: ScaleCo…
#> 3 3         1     3 <list …  1.33  7.27  10.4  45.6 <S3: ScaleCo… <S3: ScaleCo…
#> 4 4         2     1 <list …  1.33  7.27  10.4  45.6 <S3: ScaleCo… <S3: ScaleCo…
#> 5 5         2     2 <list …  1.33  7.27  10.4  45.6 <S3: ScaleCo… <S3: ScaleCo…
#> 6 6         2     3 <list …  1.33  7.27  10.4  45.6 <S3: ScaleCo… <S3: ScaleCo…
#> 7 7         3     1 <list …  1.33  7.27  10.4  45.6 <S3: ScaleCo… <S3: ScaleCo…summarise_coord(b)#> $xlog #> [1] NA #> #>$ylog
#> [1] NA
#>
#> \$flip
#> [1] FALSE
#> summarise_layers(b)#> # A tibble: 1 x 1
#>   mapping
#>   <list>
#> 1 <list [2]>