Is there a way to specify that a custom_annotation only applies to one facet of a ggplot?
For example, if I run the following code
library(tidyverse)
library(grid)
text_grob=grobTree(textGrob("text",x=0.5, y=0.6, rot=90,
gp=gpar(col="red")))
ggplot(mtcars, aes(x=mpg, y =drat))+
geom_point() +
facet_wrap(~cyl) +
annotation_custom(overrep_grob)
I get this
How can I only keep the rightmost red "text" annotation and not add the "text" annotation to the first two facets? Note I can't use geom_text or annotate because I need to make use of textGrob's relative text positioning
egg has geom_custom,
library(ggplot2)
library(grid)
library(egg)
d = data.frame(cyl=6, drat = 4, mpg = 15)
d$grob <- list(textGrob("text",rot=90, hjust = 0, gp=gpar(col="red")))
ggplot(mtcars, aes(x=mpg, y=drat))+
geom_point() +
facet_wrap(~cyl) +
geom_custom(data = d, aes(data = grob), grob_fun = identity)
You could also do this using geom_text by calculating the relative position of the text needed. Note that here, the relative position is slightly different than the one you use above because here I define the relative position as some proportion of the dynamic range. You can choose a different value for rel to get the position you need. I find that this way makes the positioning less arbitrary.
library(tidyverse)
rel_pos <- function(.data, var, rel){
var <- enquo(var)
.data %>%
summarise(x = sum(max(!!var), min(!!var))* rel) %>% .[1, "x"]
}
my_text <- data_frame(mpg = rel_pos(mtcars, mpg, 0.5),
drat = rel_pos(mtcars, drat, 0.6) ,
cyl = 8, lab = "text")
ggplot(mtcars, aes(x=mpg, y =drat))+
geom_point() +
facet_wrap(~cyl)+
geom_text(data = my_text, aes(label = lab), color = "red", angle = 90)
Created on 2018-08-15 by the reprex
package (v0.2.0).
Related
I am trying to make a ggplot2 graph in which I have a "classic" dot plot together with a table.
This is an example of the plot I am making:
library(dplyr)
library(tibble)
library(ggplot2)
library(ggpmisc)
mtcars[1:10,] %>%
select(cyl, mpg, wt) -> tb
df <- tibble(x = 5.45, y = 34, tb = list(tb))
# using defaults
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) +
geom_point() +
geom_table(data = df, aes(x = x, y = y, label = tb))
This is the output of the code:
I would however the rows of the table be coloured according to the factor cyl. So every rows which has carb==4 is red, ==6 is green and ==8 is blue.
I don't need the column cyl to appear in the table, so that can be removed (if possible).
Is there a way to do it?
Thanks a lot in advance for your precious help,
Luca
Unlike most of the ggplot ecosystem, you can't just use a fill aesthetic inside geom_table, and instead need to create a table theme which gets passed to table.theme inside geom_table. This means it is somewhat inconvenient to achieve the desired effect, but it is possible with something like the following:
thm <- gridExtra::ttheme_default()
fills <- scales::hue_pal()(3)[as.numeric(factor(df$tb[[1]]$cyl))]
thm$core$bg_params$fill <- fills
df$tb[[1]] <- df$tb[[1]][-1]
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) +
geom_point() +
geom_table(data = df, aes(x = x, y = y, label = tb), table.theme = thm)
It is a bit hacky, but using the table.theme argument, you can supply the table with your own background colors (see Controlling the colors of rows in ggplot table annotation).
First, we construct a vector which contains a required background color for each row. Then, we use those colors in the table.theme argument of geom_table.
library(dplyr)
library(tibble)
library(ggplot2)
library(ggpmisc)
mtcars[1:10,] %>%
select(cyl, mpg, wt) -> tb
df <- tibble(x = 5.45, y = 34, tb = list(tb))
# Construct vector of required background colors (from default ggplot2 theme)
colors <- scales::hue_pal()(n_distinct(tb$cyl))
colors <- colors[factor(tb$cyl)]
# using defaults
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl), fill = factor(cyl))) +
geom_point() +
geom_table(data = df, aes(x = x, y = y, label = tb),
table.theme = gridExtra::ttheme_default(core = list(bg_params=list(fill=colors))))
I have a set data that I need to add to levels of labels. One on a single chart within the facet grid, and one from a small dataframe with entries for for each chart.
In the example below you'll see that I can add to a single chart no problem but when I try to add from the df I get the error -
Error in FUN(X[[i]], ...) : object 'wt' not found
Preparation:
library(ggplot2)
p <- ggplot(mtcars, aes(mpg, wt)) + geom_line()
p <- p + facet_grid(. ~ cyl)
ann_text <- data.frame(mpg = 30,wt = 5,lab = "Text",
cyl = factor(8,levels = c("4","6","8")))
dfl <- data.frame(name = c('Jim',"Bob", "Sue"), r = c(-0.2, 0.5, -0.4))
Single Label:
p + geom_text(data = ann_text,label = "Text")
Multiple Labels:
p + geom_text(data = ann_text,label = "Text") +
geom_text(data = dfl, mpg = 30,wt = 5, aes(label = r))
The method I'm using is trying to recreate other examples I've found here on SO and elsewhere but I seem to be missing something.
It's not working in your second code because in the second geom_text, your mpg and wt in not in aes(). Also, these two variables are absent in your dfl.
If you wish to have better control of the labelling of your r variable, you can create extra columns in dfl specifying the x and y location of the label, and use these variables in geom_text(aes()).
Note that I have modified the y position in the second geom_text to avoid overlapping "0,2" with "Text".
library(ggplot2)
p <- ggplot(mtcars, aes(mpg, wt)) + geom_line()
p <- p + facet_grid(. ~ cyl)
ann_text <- data.frame(mpg = 30,wt = 5,lab = "Text",
cyl = factor(8,levels = c("4","6","8")))
dfl <- data.frame(name = c('Jim',"Bob", "Sue"), r = c(-0.2, 0.5, -0.4))
p + geom_text(data = ann_text,label = "Text") +
geom_text(data = dfl, aes(30, 4, label = r), check_overlap = T)
Created on 2022-05-06 by the reprex package (v2.0.1)
I am facing a smal issue concerning positioning labels on an R graph. I made an example with the data available in ggplot2 package to make it executable.
library(ggrepel)
library(ggplot2)
library(tidyverse)
pos <- position_jitter(seed = 1, height = 0.25)
ggplot(mtcars, aes(vs, wt, group = am, label = wt)) +
geom_jitter(position = pos) +
geom_text_repel(aes(label = ifelse(wt > 3, wt, "")), position = pos)
I used the command position_jitter to define jitter and geom_text_repel to set data labels. Using position_jitter I cannot define a position nudge_y of data labels but I woukld like to add to the defined position (position_jitter(seed = 1, height = 0.25)) a fixed value, let's say +0.5, so as to shift up systematically every label of a defined value.
Is it possible to make in R something like this?
Thank you in advance for every your reply!
RE: comments
You can manually add jitter (random uniform) noise to your datapoints beforehand. Nudging the text then becomes trivial.
library(ggrepel)
library(ggplot2)
library(tidyverse)
mtcars %>%
mutate(jit_vs = vs + runif(length(vs), -0.4, 0.4),
jit_wt = wt + runif(length(wt), -0.25, 0.25)) %>%
ggplot(aes(jit_vs, jit_wt, group = am, label = wt)) +
geom_point() +
geom_text_repel(aes(label = ifelse(wt > 3, wt, "")), nudge_y = 0.5)
Created on 2021-09-03 by the reprex package (v2.0.1)
I'm plotting data marked up using haven semantics, i.e. variables and values have labels defined via attributes.
Often, these labels are also what I want in my axis titles and ticks.
library(ggplot2)
mtcars$mpg = haven::labelled(mtcars$mpg, labels = c("low" = 10, "high" = 30))
attributes(mtcars$mpg)$label = "miles per gallon"
ggplot(mtcars, aes(mpg, cyl)) + geom_point() +
scale_x_continuous(attributes(mtcars$mpg)$label,
breaks = attributes(mtcars$mpg)$labels,
labels = names(attributes(mtcars$mpg)$labels))
Could I write a helper that replaces that laborious scale_x_continuous statement with something that can more easily be iterated? E.g. something like
scale_x_continuous(label_from_attr, breaks = breaks_from_attr, labels = value_labels_from_attr). Or maybe even + add_labels_from_attributes() to replace the whole thing?
I'm aware that I can write/use helpers like Hmisc::label to slightly shorten the attribute-code above, but that's not what I want here.
I don't have a good scale, but you can use a function like this:
label_x <- function(p) {
b <- ggplot_build(p)
x <- b$plot$data[[b$plot$labels$x]]
p + scale_x_continuous(
attributes(x)$label,
breaks = attributes(x)$labels,
labels = names(attributes(x)$labels)
)
}
Then use as (+ won't do):
p <- ggplot(mtcars, aes(mpg, cyl)) + geom_point()
label_x(p)
Alternatively, use a pipe:
mtcars %>% { ggplot(., aes(mpg, cyl)) + geom_point() } %>% label_x()
Old solution
use_labelled <- function(l, axis = "x") {
if (axis == "x") {
scale_x_continuous(attributes(l)$label,
breaks = attributes(l)$labels,
labels = names(attributes(l)$labels))
}
if (axis == "y") {
scale_y_continuous(attributes(l)$label,
breaks = attributes(l)$labels,
labels = names(attributes(l)$labels))
}
}
Then you just give:
ggplot(mtcars, aes(mpg, cyl)) + geom_point() + use_labelled(mtcars$cyl)
Or for the y-axis:
ggplot(mtcars, aes(cyl, mpg)) + geom_point() + use_labelled(mtcars$cyl, "y")
Another approach is to write a wrapper for ggplot() that has its own class. Then attributes have full visibility when the corresponding print method is called. See ?ag.print from package 'yamlet' (0.2.1).
library(ggplot2)
library(yamlet)
library(magrittr)
mtcars$disp %<>% structure(label = 'displacement', unit = 'cu. in.')
mtcars$mpg %<>% structure(label = 'mileage', unit = 'miles/gallon')
mtcars$am %<>% factor(levels = c(0,1), labels = c('automatic','manual'))
mtcars$am %<>% structure(label = 'transmission')
agplot(mtcars, aes(disp, mpg, color = am)) + geom_point()
On the below plot, I'd like to create an empty space on the x-axis at position 3. In other word, I'd like that the dots for wt>=3 and the axis scale when wt>=3 are shifted to the right side by some arbitrary chosen value. Does it make sense?
ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
I could simply modify the my data and add 0.5 to each value of mpg where wt>=3 but it doesn't solve the issue with the x-axis.
I might rephrase my question saying that on the below graph I'd like that the vertical line does not overlap the data and therefore all the data (and also the x-axis) should be shifted to the left by the thickness of the vertical line.
ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + geom_vline(xintercept=3, size=30)
I was thinking about facet_wrap or viewport. Maybe something like adding a constant to each value of mpg where wt>=3 and then, manually set the values for the x-axis.
Not entirely sure what you are looking for, and I get confused by watching the weird axis on my own plot... Something like this?
mtcars$wt2 <- with(mtcars, ifelse(wt > 3, wt+1, wt))
ggplot(mtcars, aes(x = wt2, y = mpg)) +
geom_point() +
annotate("rect", xmin = 3, xmax = 4, ymin = 0, ymax = 35, alpha = 0.2) +
scale_x_continuous(breaks = round(mtcars$wt2), label = round(mtcars$wt))
Similar to # Frank, and tested...
x <- mtcars
x$group <- ""
x[x$wt<3,]$group <- "1.LIGHT"
x[x$wt>=3,]$group <- "2.HEAVY"
library(ggplot2)
library(grid) #for unit(...)
ggplot(x, aes(x=wt,y=mpg)) +
geom_point() +
facet_grid(~group,scales="free",space="free") +
theme(panel.margin = unit(2, "lines"))
Produces this:
what about something like this?
mtcars <- transform(mtcars, split = ifelse(wt >= 3, "b", "a" ))
ggplot(mtcars, aes(x = wt, y = mpg)) +
geom_point() +
facet_wrap(~split, scales = "free_x")