I want to add a single point to only one facet. I tried to set the group in geom_point:
ggplot(data=mpg, aes(displ, hwy)) +
geom_point() +
facet_wrap(~class) + geom_point(aes(x=5, y=25, group = "pickup"), colour="blue")
But that put a blue dot in all facets. Is there any way to constrain the point to only one?
You could achieve your desired result by putting the information for your point in a dataframe which you pass to the data argument of your second geom_point:
library(ggplot2)
ggplot(data=mpg, aes(displ, hwy)) +
geom_point() +
facet_wrap(~class) +
geom_point(data = data.frame(displ = 5, hwy = 25, class = "pickup"), colour="blue")
Related
How can we set the breaks of continous axis every 2 numbers if we have a very big range of values in an axis and cannot set it manually?
p1 <- ggplot(mpg, aes(displ, hwy)) +
geom_point()
p1 + scale_x_continuous(breaks = c(2, 4, 6))
From the ?scale_x_continuous help page, breaks can be (among other options)
A function that takes the limits as input and returns breaks as output
The scales package offers breaks_width() for exactly this purpose:
ggplot(mpg, aes(displ, hwy)) +
geom_point() +
scale_x_continuous(breaks = scales::breaks_width(2))
Here's an anonymous function going from the (floored) min to the (ceilinged) max by 2:
ggplot(mpg, aes(displ, hwy)) +
geom_point() +
scale_x_continuous(breaks = \(x) seq(floor(x[1]), ceiling(x[2]), by = 2))
Alternately you could still use seq for finer control, more customizable, less generalizable:
ggplot(mpg, aes(displ, hwy)) +
geom_point() +
scale_x_continuous(breaks = seq(2, 6, by = 2))
How can I annotate the following plot? I want to include counts on top of each bar.
g <- ggplot(mpg, aes(class))
# Number of cars in each class:
g + geom_bar()
I only know how to do it if I do a group by and create a new column 'count' for example.
You can do:
ggplot(mpg, aes(class)) +
geom_bar() +
geom_text(stat = "count", aes(label = after_stat(count)), nudge_y = 1)
I refer to section 12.2.4, exercise 1 in Hadley Wickham's ggplot2 book.
In the exercise, the following code is provided:
fwd <- subset(mpg, drv == "f")
rwd <- subset(mpg, drv == "r")
ggplot(fwd, aes(displ, hwy, colour = class)) + geom_point()
ggplot(rwd, aes(displ, hwy, colour = class)) + geom_point()
Which produces the following output:
The following task is given: Modify the code so that the legend and axes match, without using facetting!
I am able to modify so that the axes match:
ggplot(fwd, aes(displ, hwy, colour = class)) + geom_point() + xlim(c(0, 7)) + ylim(c(0, 45))
ggplot(rwd, aes(displ, hwy, colour = class)) + geom_point() + xlim(c(0, 7)) + ylim(c(0, 45))
yielding:
But, I'm unable to get the legends to match. This question comes before scale_colour_manual() is explained, so I don't think we're supposed to use that.
Any ideas about how to get the legends to match?
Thanks!
I recently started learning R but am confused with the aes feature in ggplot2.
I have seen two different places where aes is placed in the code.
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy))
ggplot(mpg, aes(x = displ, y = hwy)) +
geom_point()
What is the difference between the two?
Can't find a dupe, so here's an answer:
Aesthetics specified in ggplot() are inherited by subsequent layers. Aesthetics specified in particular layers are specific only to that layer. Here's an example:
library(ggplot2)
ggplot(mtcars, aes(wt, mpg)) +
geom_point() +
geom_smooth()
ggplot(mtcars) +
geom_point(aes(wt, mpg)) +
geom_smooth() # error, geom_smooth needs its own aesthetics
This is mostly useful when you want different layers to have different specifications, for example these two plots are different, you have to decide which you want:
ggplot(mtcars, aes(wt, mpg, color = factor(cyl))) +
geom_point() +
geom_smooth()
ggplot(mtcars, aes(wt, mpg)) +
geom_point(aes(color = factor(cyl))) +
geom_smooth()
On individual layers, you can use inherit.aes = FALSE to turn off inheritance for that layer. This is very useful if most of your layers use the same aesthetics, but a few do not.
I am new to ggplot. I am trying to understand how to use ggplot. I am reading Wickham's book and still trying to wrap my head around how to use aes() function.
What's the difference between these two implementations of aes():
library(ggplot2)
ggplot(mpg, aes(displ, hwy, colour = class)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE) +
theme(legend.position = "none")
and
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(colour = class)) +
geom_smooth(method = "lm", se = FALSE) +
theme(legend.position = "none")
Both of them print significantly different graphs. Any help? I am really stuck.
In the first one you are mapping the aesthetics globally, ggplot will try to map these aesthetics to all other geom_xyz() layers.
While in the latter case, you are mapping aesethics to a specific ggplot layer (in your case geom_point())