Is it possible to only shown point labels in the zoom-in panel (without showing point labels in the original panel)?

Is that absolutely necessary? It makes to recommend to students or colleagues

Hi,

geom_sina() is a good alternative to geom_boxplot(), how can I add the median line to sina plot as boxplot does?

I know I can lay over boxplot over it
ggplot(df, aes(Distribution, Value)) + geom_violin(aes(fill = Distribution)) + geom_boxplot()

or add a summary, but only using a point:

stat_summary(fun.y=median, geom="point", fill= "white", shape = 21, size =2.5)
what if I just want a short median line ?

Thanks very much,
Tommy

ggplot2 isn't released very often in the last few years, do you know if Hadley has plans of releasing it soon?

I was wondering why not releasing the paginate functions and simply specify the dev version of ggplot2 in the DESCRIPTION and travis. Of course it's a very selfish request :)

Hi,
I'm finally getting to look at ggforce as a basis for implementing connectograms, as you suggested back in july in response to a ggplot2 query.

The stat_pie structures actually look like they are very close to doing most of what I need to get started.

I'm still finding my way around the package code, so thought I'd make some queries before doing anything to stupid.

My first couple of changes were to look at options for changing direction (clockwise/counter clockwise) and orientation (vertical/horizontal). I can see that radial_trans has an offset option, but can't see
a way of setting it from a geom_arc_bar call. Also, is there a direction option hidden away? I had a quick go at adding such options but they interacted with "explode".

Finally, do you know of a way of checking what values (e.g. new dataframe columns) are computed internally by various stat_ without checking the code? I know you have some documentation but I was wondering about a ggplot way.

Finally, I think the only thing missing from the current code to implement connectograms is something giving the midpoint of the arcs. This is needed for links and labels. Looks like it should be easy enough to do, but thought I should check that it isn't already there somewhere.

Thanks

while creating choropleth maps and using geom_polygon to visualize spatial data, I have been looking for a way to use ggplot2 to draw a bar/pie chart at the centroids of each/selected polygons with stat = "identity"

library(dplyr)
library(ggplot2)
df <- data.frame(Region.ID = LETTERS[1:5],
                 Population.mill = sample(15:21, 5),
                 Male = sample(8:12, 5))
df <- df %>%
  mutate(Female = Population.mill - Male)
head(df)

For instance, in this data df, how would you add a pie/bar to show Male against Female for each/selected observation(s)? I know that I could play around with the base function plot() and a few other packages but my goal is to harness on the power and flexibility of ggplot2 to achieve the same.

Currently the alpha value for strip.background in facet_zoom is hard-coded to .5 -- even if a scales::alpha is passed in for the fill arg. Is it possible to allow the user to change that?

geom_blob()?

Following our Twitter exchange, I would love to have a geom_bag for a bivariate box plot. I previously mentioned this on ggalt, and made a start, but I'm not sure how to finish it. Also, I think there might be a better implementation in the code for this paper. What do you think?

facet_zoom() points at something important lacking in ggplot2: a tool to link across figure panels.

Would there be a way to use facet_zoom() in which the zoomed area could be populated with different plots altogether?

Concretely, this could be used when:

• the data from the zoomed area (a subset of the data in the original panel) are used to produce a different visualisation, and we want to indicate the origin of the data;

• all the data from the original panel are used in a different calculation, leading to a different visualisation in which the units cover a subset of the original units - for instance a linear fit is performed using all the data, but in the zoomed area we investigate the residuals in one area of the fit only.

http://stackoverflow.com/questions/35717353/split-violin-plot-with-ggplot2

Like geom_violin but with an extra argument split = var
Often useful for comparing men vs women etc.

Using the units package we can associate (physical) units to quantities and guarantee that we only do arithmetic on compatible units. Plotting data with associated units, however, is cumbersome in ggplot. Can we make ggplot unit-aware?

(Copied from here)

We need a geom_sf() to render simple feature objects in ggplots, e.g. where

nc = st_read(system.file("shape/nc.shp", package="sf"))
ggplot() + geom_sf(nc)

would add the polygon boundaries, and further argument can alter the color of polygons and polygon boundaries, as well as point and line geometries. I wrote some building blocks, basically functions that convert sf objects into grid grobs here and am willing to help out, but would appreciate some help getting started from someone who's been here before: @thomasp85, @hadley, @mdsumner , @hrbrmstr?

Issues to keep in mind:

• can geom_sf control the aspect ratio used, such that 1 km north equals 1 km east?
• when combining with ggmap(), I think web mercator is assumed: automatically use st_transform?
• when combining different geom_sfs, can we verify that coordinate reference systems correspond?

Occurs with both v0.1.0 and the master branch.

Minimal example:

library(ggplot2)

library(ggforce)

df <- data.frame(
    x = rep(1:10, each = 100),
    y = rnorm(10000)
)

ggplot(df, aes(x = factor(x), y = y)) + geom_sina()

Works.

ggplot(df, aes(x = x, y = y)) + geom_sina()

Produces the following error instead of complaining about a continuous x aesthetic: Error in f(...) : could not find function "has_groups".

facet_shingles()

a minor glitch
devtools::install_github('thomasp85/ggforce') Downloading GitHub repo thomasp85/ggforce@master from URL https://api.github.com/repos/thomasp85/ggforce/zipball/master Fehler in eapply(ns_env(pkg), force, all.names = TRUE) : kann Datei '/Library/Frameworks/R.framework/Versions/3.3/Resources/library/ggforce/R/ggforce.rdb' nicht öffnen: No such file or directory

Repeat plot but gradually subset data in a nested fashion

• Let the user specify a scale range directly
• Make it possible to have elements that only shows in the zoomed in panel

A range of geoms for marking an area containing points:

• geom_mark_hull()
• geom_mark_rect()
• geom_mark_ellipsis()

ggalt has geom_xspline() which might fulfill the needs of your pending geom_spline()

Great package!

So I often use geom_violin or geom_boxplot to look at just one category. The standard way I do this is with something like the following

ggplot(df, aes(x=1, y=Var)) + geom_violin()

However, when trying to use geom_sina, I had to create a useless variable, because otherwise, I got the following error:
Error in f(...) : could not find function "has_groups"

The solution I've found, for now, is just the following:

df$Varx <- "Varx"
ggplot(df, aes(x=Varx, y=Var)) + geom_sina()

Thanks for the awesome package,
Gaius

I'm having an issue with geom_sina (a package which I love, by the way) where if there is only one value that value is omitted. Here is a reproducible example:

simple <- data.frame(ID = c(rep(1,7)),
                     group = c("alpha", "beta", "alpha", "beta", "alpha", "beta", "alpha"),
                     version = c("on", "on", "off", "off", "on", "on", "off"),
                     value = c(1:4, 1:3))

ggplot() +   
    geom_point(data = simple, aes(x = ID, y = value, colour = ID),
               position = position_jitter(w = 0.2, h = 0)) +
    theme(legend.position = "none",
          axis.title.y = element_blank()) +
    facet_grid(version ~ group, shrink=FALSE)

ggplot() +   
    geom_sina(data = simple, aes(x = ID, y = value, colour = ID)) +
    theme(legend.position = "none",
          axis.title.y = element_blank()) +
    facet_grid(version ~ group, shrink=FALSE)

That creates two plots. The geom_point plot has all points, but the geom_sina one has omitted the single point in 'beta' x 'off' and gives the following warning:

Warning message:
Removed 1 rows containing missing values (geom_sina).

I suspect the removed row is the single point I wanted plotted. Is there a workaround or fix?

Thanks!

(Edited to fix sample data set)

Nice work on ggforce and looking forward to the new release with ggplot2 2.2.0. In the meantime 2 questions on facet_wrap_paginate:

• Is it possible to print all pages at once without using the for loop?
• Is it possible to keep the requested layout e.g. ncol = 2, nrow = 2 on the last page even if there is in this case only 2 panels left to plot?

When the data is split by colour, then geom_sina should split the data like geom_violin does, but the points stay in the same x position.

df <- data.frame(a=sample(LETTERS[1:6],1000,replace=TRUE), b=rnorm(1000),l=c(TRUE,FALSE))
ggplot(df, aes(x=a,y=b,colour=l)) + geom_violin() + geom_sina()

I tried to test some things and geom_violin copes with my stupid test data, but geom_sina throws errors. Maybe thats indicative of some problems - I don't really know.

df <- data.frame(g=c("A","B"),v=rep(c(rep(5,20),rep(10,20),rep(15,20)),2))
ggplot(df, aes(x=1,y=v)) + geom_violin()
ggplot(df, aes(x=1,y=v)) + geom_sina() //Error in f(...) : could not find function "has_groups"
ggplot(df, aes(x=g,y=v)) + geom_violin()
ggplot(df, aes(x=g,y=v)) + geom_sina() //Warning: Computation failed in `stat_sina()`: 'vec' must be sorted non-decreasingly and not contain NAs

I was very happy to see your demo if facet_zoom() on twitter. I didn't have a real application to test it until yesterday. And I would like to zoom in based on a chosen on the response raw scale with a numerical vector.

Before I was using grid.arrange

gridExtra::grid.arrange(rr, rr + coord_cartesian(ylim = c(609, 611)) + theme(legend.position = "none"), nrow = 1, widths = c(0.65, 0.35))

Then, I tried facet_zoom using a naive approach
ggforce::facet_zoom(y = c(500, 680), shrink = FALSE, zoom.size = 0.75)

It looks roughly ok, but:

• it introduced missing data, the naive approach does not create the appropriate logical vector to subset
• the zoom is on the left, would prefer it on the right and exchange the legend
• the chosen y-scale fits the dashed lines but are too zoomed in
  

the final idea was to create the logical vector on the continuous response using dplyr::between

ggforce::facet_zoom(y = between(biomass, 609, 611), shrink = FALSE, zoom.size = 0.75)

but it is not like coord_cartesian to zoom in the plot, but select data.

the best I achieved was

the code is there:

library(tidyverse)
read_tsv("https://raw.githubusercontent.com/LSRU/r_workshop/gh-pages/data/competition.txt") %>%
  ggplot(aes(x = clipping, y = biomass)) + geom_boxplot() + labs(x = "Competition treatment", colour = NULL, y = "Biomass") +
  geom_hline(aes(colour = "mean r10", yintercept = 610.6667), linetype = "dashed") +
  geom_hline(aes(colour = "clipping3", yintercept = 610.6667 - 0.08333), linetype = "dashed") +
  geom_hline(aes(colour = "mean (r5, r10)", yintercept = (610.6667 + 610.5) / 2), alpha = 0.6) +
  geom_hline(aes(colour = "mean r5", yintercept = 610.5), linetype = "dashed") + # -> rr
  #ggforce::facet_zoom(y = c(500, 680), shrink = FALSE, zoom.size = 0.75)
  ggforce::facet_zoom(y = between(biomass, 600, 615), shrink = FALSE, zoom.size = 0.75)

Thanks again for all the very nice developments you did!

Using devtools::install_github("thomasp85/ggforce") does not work for me. The process hangs and cannot be interrupted.
I am using R version 3.3.2 on a linux machine.

Thanks for this nice additions. I noticed a minor issue with the geom_sina function that wanted to bring to your attention. It's probably a scaling vs width issue.

I have several hundred datapoints in the range -2000 to 6000. When I plot my datapoints using geom_sina(size=1) without any additional options, I don't get any jitter (or if there is, the default width is too small to notice). Visually they all line up in a straight line.

When I re-scale my data to range -2 to 6 (divide by 1000), I get a nice jitter with appropriate width. The geom_violin function works fine with appropriate width without a need to re-scale my data, but geom_sina doesn't. It should be easy to replicate on your end, but I can send you my data values if you like.

With automatic conversion

with geom_circle() adding scale_*_reverse() seems to do a multiply by -1 transformation and not a reverse the axis transformation as expected (i.e. what happens in other ggplot2 geoms)

library(ggforce)
#> Loading required package: ggplot2
d <- data.frame(x0 = 1, y0 = 1, r = 0.5)

ggplot(d) + geom_circle(aes(x0 = x0, y0 = y0, r = r))

ggplot(d) + geom_circle(aes(x0 = x0, y0 = y0, r = r)) + scale_y_reverse()

ggplot(d) + geom_circle(aes(x0 = x0, y0 = y0, r = r)) + scale_x_reverse()

devtools::session_info()
#> Session info --------------------------------------------------------------
#>  setting  value                       
#>  version  R version 3.3.2 (2016-10-31)
#>  system   x86_64, darwin16.1.0        
#>  ui       unknown                     
#>  language (EN)                        
#>  collate  en_CA.UTF-8                 
#>  tz       America/Vancouver           
#>  date     2016-12-06
#> Packages ------------------------------------------------------------------
#>  package    * version date       source        
#>  assertthat   0.1     2013-12-06 CRAN (R 3.3.2)
#>  backports    1.0.4   2016-10-24 CRAN (R 3.3.2)
#>  colorspace   1.3-1   2016-11-18 CRAN (R 3.3.2)
#>  DBI          0.5-1   2016-09-10 CRAN (R 3.3.2)
#>  devtools     1.12.0  2016-06-24 CRAN (R 3.3.2)
#>  digest       0.6.10  2016-08-02 CRAN (R 3.3.2)
#>  dplyr        0.5.0   2016-06-24 CRAN (R 3.3.2)
#>  evaluate     0.10    2016-10-11 CRAN (R 3.3.2)
#>  formatR      1.4     2016-05-09 CRAN (R 3.3.2)
#>  ggforce    * 0.1.1   2016-11-28 CRAN (R 3.3.2)
#>  ggplot2    * 2.2.0   2016-11-11 CRAN (R 3.3.2)
#>  gtable       0.2.0   2016-02-26 CRAN (R 3.3.2)
#>  htmltools    0.3.5   2016-03-21 CRAN (R 3.3.2)
#>  knitr        1.15.1  2016-11-22 CRAN (R 3.3.2)
#>  labeling     0.3     2014-08-23 CRAN (R 3.3.2)
#>  lazyeval     0.2.0   2016-06-12 CRAN (R 3.3.2)
#>  magrittr     1.5     2014-11-22 CRAN (R 3.3.2)
#>  MASS         7.3-45  2016-04-21 CRAN (R 3.3.2)
#>  memoise      1.0.0   2016-01-29 CRAN (R 3.3.2)
#>  munsell      0.4.3   2016-02-13 CRAN (R 3.3.2)
#>  plyr         1.8.4   2016-06-08 CRAN (R 3.3.2)
#>  R6           2.2.0   2016-10-05 CRAN (R 3.3.2)
#>  Rcpp         0.12.8  2016-11-17 CRAN (R 3.3.2)
#>  rmarkdown    1.2     2016-11-21 CRAN (R 3.3.2)
#>  rprojroot    1.1     2016-10-29 CRAN (R 3.3.2)
#>  scales       0.4.1   2016-11-09 CRAN (R 3.3.2)
#>  stringi      1.1.2   2016-10-01 CRAN (R 3.3.2)
#>  stringr      1.1.0   2016-08-19 CRAN (R 3.3.2)
#>  tibble       1.2     2016-08-26 CRAN (R 3.3.2)
#>  tweenr       0.1.5   2016-10-10 CRAN (R 3.3.2)
#>  udunits2     0.13    2016-11-17 CRAN (R 3.3.2)
#>  units        0.4     2016-11-21 CRAN (R 3.3.2)
#>  withr        1.0.2   2016-06-20 CRAN (R 3.3.2)

The shading on the full data panel which indicates the axis range on the zoom panel doesn't fully cover the axis range actually used in the zoom panel.

df <- data.frame(weight = c(1.2, 2.5, 3.6, 4.0, 4.5), outcome = c(20, 2100, 200, 10, 2500))

ggplot(df, aes(weight, outcome)) +
  geom_point() +
  facet_zoom(y = outcome < 300)

Is it possible to have zoomed region to have different Y values and different type of plot?

Example:

library(ggplot2)
library(ggforce)

#dummy data
set.seed(1)
df1 <- data.frame(x = 1:100, y = runif(100), zoom = c(rep("a", 30), rep("b", 20), rep("c", 50)))
df2 <- data.frame(x = 1:100, y = runif(100, 1, 10))

ggplot(df1, aes(x, y)) +
  geom_point() + 
  facet_zoom(x = zoom == "b")

All great but this is not what I want. I need to have the zoomed region to have plot based on different data as Y value, and different plot type:

gg1 <- ggplot(df1, aes(x, y)) + geom_point()
gg2 <- ggplot(df2, aes(x, y)) + geom_line()

#interseting area zoomed in with line plot
range(df1[ df1$zoom == "b", "x"])
# [1] 31 50
gg2zoom <- ggplot(df2[ df2$x >= 31 & df2$x <= 50, ], aes(x, y)) + 
  geom_line()

#merge plot vertically
cowplot::plot_grid(gg1, gg2zoom, nrow = 2)

I would want above plot with your type of shading to show zooming area, here is expected output with bit of Paintburshing:

Possible? Maybe other workarounds?

Is there a nice way to combine facet_zoom with coord_quickmap? I'd like to have a combination of the first plot with a zoom in around the UK. When I try to use facet_zoom, I can either forgo the call to coord_quickmap and get the correct zoom, but a weird aspect ratio (ex 2) or I can include coord_quickmap but then while the zoom facet has the right aspect ratio, it shows the whole map (ex 3)

library(ggforce)
#> Loading required package: ggplot2
library(maps)

global_map <- map_data("world")

point_data <- data.frame(lng = c(runif(50, -10, -3), runif(50, -50, -3)), lat = c(runif(50, 
  54, 60), runif(50, 54, 65)))

p <- ggplot() + geom_polygon(aes(x = long, y = lat, group = group), fill = "#4FFFB0", 
  colour = NA, data = global_map) + theme(panel.grid = element_blank(), panel.background = element_rect(fill = "#0087BD")) + 
  geom_point(aes(x = lng, y = lat, colour = pct_change), colour = "yellow", 
    data = point_data)

p + coord_quickmap(xlim = c(-52.25, -5), ylim = c(54.5, 64.5))

p + facet_zoom(xlim = c(-10, -3), ylim = c(54, 60), horizontal = FALSE)

p + facet_zoom(xlim = c(-10, -3), ylim = c(54, 60), horizontal = FALSE) + coord_quickmap(xlim = c(-52.25, 
  -5), ylim = c(54.5, 64.5))

(In the github description)

I think I read somewhere the bracket in units label x [km] can be changed to parenthesis x (km), but I cannot find it anymore.

x and y should all be provided

If only provide x or y, it fails even with the example you posted in twitter.

> p + facet_zoom(x = Species != 'setosa', y = Species == 'versicolor')
> p + facet_zoom(y = Species == 'versicolor')
Error in x_scales[[2]] : subscript out of bounds

fail if it was wrapped in a function

require(ggtree)
tr <- rtree(50)
p <- ggplot(tr, aes(x, y)) + geom_tree2() + geom_label(aes(label=node))

tree_zoom <- function(treeview, node, ...) {    
    treeview + facet_zoom(xy = node %in% get.offspring.df(treeview$data, node), ...)
}

tree_zoom(ggplot(tr, aes(x, y)) + geom_tree2() + geom_label(aes(label=node)), node=84)

ugly when not using theme_grey

p1 <- ggplot(tr, aes(x, y)) + geom_tree2() + geom_label(aes(label=node))+ theme_tree()
p1 <- p1 + facet_zoom(xy = node %in% get.offspring.df(p1$data, 84))

multiplot(p1, p1+theme_grey(), ncol=2)

For putting axes in the plot area automatically

The following example in the vignette has the wrong y-axis values in the zoom plot

ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) +
    geom_point() +
    facet_zoom(xy = Species == "versicolor")

Similar but different to #56. With geom_sf() on its way to ggplot2 it would be great to have projection-aware facet_zooming. Part of this would likely require that the original and zoomed panels not necessarily be the same height/width, in order to maintain projections. For example, it would be great to be able to zoom a region of a map

library(dplyr)
library(maps)
library(ggplot2) 
library(ggforce) 
aus_map <- map_data("world") %>% 
  filter(region == "Australia", 
         is.na(subregion) | subregion %in% c("Tasmania", "Kangaroo Island"))
p <- ggplot() + 
  geom_polygon(aes(x = long, y = lat, group = group), 
               colour = NA, 
               data = aus_map) 
p + facet_zoom(xlim = c(131, 148), ylim = c(-45, -32), 
               zoom.size = 4)

Attempting to do similar with the sf branch of ggplot2 just produces the unzoomed map in both panels and seems to miss the zoom highlight, though it certainly looks neater.

library(sf)      
library(maps)
library(ggplot2) # devtools::install_github("tidyverse/ggplot2@sf") ## NOTE sf branch
library(ggforce)
world1 <- sf::st_as_sf(map('world', plot = FALSE, fill = TRUE))
ggplot() + 
  geom_sf(data = world1) + 
  coord_sf(xlim = c(110, 160), ylim = c(-45, -10)) + 
  facet_zoom(xlim = c(132, 148), ylim = c(-45, -32))

This has potential to look really awesome if the unzoomed panel could have its height adjusted to maintain projection (width can currently be somewhat manually adjusted via zoom.size) and if the subsetting was compatible with the sf features (appropriate highlight/zoom).

I know it's a dev feature, so this is just 'down the track' thinking.

ggplot(diamonds) +
  geom_point(aes(carat, price), alpha = 0.1) +
  facet_wrap_paginate(~cut:clarity, scales = 'free', ncol=3, nrow=3, page =3)

ggplot(diamonds) +
  geom_point(aes(carat, price), alpha = 0.1) +
  facet_wrap_paginate(~cut:clarity, scales = 'free_y', ncol=3, nrow=3, page =3)

ggplot(diamonds) +
  geom_point(aes(carat, price), alpha = 0.1) +
  facet_wrap_paginate(~cut:clarity, scales = 'free_x', ncol=3, nrow=3, page =3)

All codes return an error: Error in FUN(X[[i]], ...) : Unknown input

ggplot(diamonds) +
  geom_point(aes(carat, price), alpha = 0.1) +
  facet_wrap_paginate(~cut:clarity, scales = 'fixed', ncol=3, nrow=3, page =3)

Works as intended.

as geom_point() but with pies

How to add abline to facet_zoom plot if I want to see it both on original and zoomed parts?
Currently I get this error:

ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) +
    geom_point() + facet_zoom(x = Species == "versicolor") +
    geom_abline(slope =0.3) 

Error in data.frame(..., check.names = FALSE) :
arguments imply differing number of rows: 0, 1

In producing faceted plots over multiple pages, where the final page is not entirely filled with plots, the faceting style is not always carried over. For instance, if there are 3 plots per page and final page has only a single faceted plot, instead of occupying 1/3 of the page - it takes up the whole page. Reproduced with the following code:

`# Calculate the number of pages with 3 panels per page
n_pages <- ceiling(length(levels(diamonds$cut)) * length(levels(diamonds$clarity)) / 3)'

'# Draw each page
for (i in seq_len(n_pages)) {
print(ggplot(diamonds) +
geom_point(aes(carat, price), alpha = 0.1) +
facet_wrap_paginate(~cut:clarity, ncol = 3, nrow = 1, scales = "fixed", page = i))
}`

It goes from page 13 - in the above case:

to page 14 - the last page:

When the number of plots per page are changed - we end up with another a strange arrangement of grobs (2x3 vs 3x3):

Using the following code:
`# Calculate the number of pages with 9 panels per page
n_pages <- ceiling(
length(levels(diamonds$cut)) * length(levels(diamonds$clarity)) / 9)'

'# Draw each page
for (i in seq_len(n_pages)) {
print(ggplot(diamonds) +
geom_point(aes(carat, price), alpha = 0.1) +
facet_wrap_paginate(~cut:clarity, ncol = 3, nrow = 3, scales = "fixed", page = i))
}`

Please implement geom_wordcloud. Thank you!

I noticed this whilst working with my own data. I've reproduced using the diamond df below: When scales is changed from its default ("fixed") - to (say) "free", you get the error -

Error in FUN(X[[i]], ...) : Unknown input

# Calculate the number of pages with 9 panels per page n_pages <- ceiling( length(levels(diamonds$cut)) * length(levels(diamonds$clarity)) / 9)

# Draw each page for (i in seq_len(n_pages)) { print(ggplot(diamonds) + geom_point(aes(carat, price), alpha = 0.1) + facet_wrap_paginate(~cut:clarity, ncol = 3, nrow = 3, scales = "free", page = i))

Traceback:
19 stop("Unknown input") 18 FUN(X[[i]], ...) 17 lapply(grobs, height_cm) 16 unlist(lapply(grobs, height_cm)) 15 unit(max(unlist(lapply(grobs, height_cm))), "cm") 14 FUN(newX[, i], ...) 13 apply(axis_mat_x_top, 1, max_height) 12 unit(apply(axis_mat_x_top, 1, max_height), "cm") 11 f(...) 10 FacetWrap$draw_panels(panels, layout, x_scales, y_scales, ranges, coord, data, theme, params) 9 f(...) 8 self$draw_panels(panels, layout, x_scales, y_scales, ranges, coord, data, theme, self$params) 7 f(..., self = self) 6 self$facet$render_panels(panels, self$panel_layout, self$panel_scales$x, self$panel_scales$y, self$panel_ranges, coord, data, theme, labels) 5 f(..., self = self) 4 layout$render(geom_grobs, data, plot$coordinates, theme, plot$labels) 3 ggplot_gtable(data) 2 print.ggplot(ggplot(diamonds) + geom_point(aes(carat, price), alpha = 0.1) + facet_wrap_paginate(~cut:clarity, ncol = 3, nrow = 3, scales = "free", page = i)) 1 print(ggplot(diamonds) + geom_point(aes(carat, price), alpha = 0.1) + facet_wrap_paginate(~cut:clarity, ncol = 3, nrow = 3, scales = "free", page = i))

• facet_table()
• facet_layout()

Example plots and code in README will do wonders to motivate me to install and use this. Thanks!