I would like to make a plot like the one schematized below with x-axis on a reciprocal scale and y-axis on a profit scale, ideally with ggplot2 but I haven't figured out a way to do that. Is there anyone who could help me?
You can use scales package to transform scales, functions reciprocal_trans() and probit_trans().
library(ggplot2)
library(scales)
ggplot(df, aes(x, y)) +
geom_line() +
scale_x_continuous(trans = reciprocal_trans()) +
scale_y_continuous(trans = probit_trans())
Related
Hello I am very new to using coding language and recently made my first couple of figures in R. I used this code to make the figures and they turned out good except that the labels in the x axis were overlapping.
library(ggplot2)
ggplot(LR_density, aes(x=Plant_Lines, y=`Lateral_Root_Density.(root/cm)`, fill=Expression_Type)) +
geom_boxplot() +
geom_jitter(color="black", size=0.4, alpha=0.9) +
ggtitle("Lateral root density across plant expression types")
The figure produced by the line of code I used
I was wondering if anyone knew how to get the x axis labels to be more spaced out in ggplot2 boxplots. I have been looking around but havent found a clear answer on this. Any help on what to do or where to look would be great!
As per comment, this thread shows another option to deal with overlapping x axis labels, which one can use since ggplot2 3.3.0
In included a second graph which "squeezes" the axis a bit, which kind of also simulates the effect of changing the viewport/ file size.
library(ggplot2)
ggplot(diamonds, aes(x = cut, y = price)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(n.dodge = 2))
ggplot(diamonds, aes(x = cut, y = price)) +
geom_boxplot() +
scale_x_discrete(guide = guide_axis(n.dodge = 2)) +
coord_fixed(1/10^3.4)
Created on 2020-04-30 by the reprex package (v0.3.0)
I need to plot the geom_histogram but as the plots overlap, I want to plot it linear instead of bars, i.e, the x=hp, y=count (percent).
Can anybody please help me find how to do it.
library(ggplot2)
library(scales)
ggplot(mtcars, aes(x=hp)) +
geom_histogram(binwidth=5)
I have done it by qplot but I need to do it in ggplot and the percent.
qplot(hp, data = mtcars, geom = "freqpoly", binwidth = 10)
Thanks
You can use geom_freqpoly:
library(ggplot2)
library(scales)
ggplot(mtcars, aes(x=hp, y=..count../sum(..count..))) +
geom_freqpoly(binwidth=5) +
scale_y_continuous(labels = percent_format()) +
ylab("Percent")
Is it possible to add horizontal lines from 0 to the points on the plot shown below?
This is the code thus far:
ggplot(data, aes(x=change, y=industry, color=geo)) + geom_point() +
scale_x_continuous(labels = scales::comma) + geom_vline(xintercept = 0)
Alternatively, I could use geom_bar() but I have been unsure how to show both London and the UK without them summing together.
tl;dr you can use geom_bar() with position="stack", stat="identity". Or you can use geom_segment().
set up data
dd <- expand.grid(industry=c("property",
"manufacturing",
"other"),
geo=c("London","UK"))
set.seed(101)
dd$change <- runif(6,min=-30,max=30)
This is how you could do it with geom_bar
library(ggplot2)
ggplot(dd,aes(x=industry,y=change,
fill=geo))+
geom_bar(stat="identity",
position="dodge")+
coord_flip()
Or with geom_segment():
ggplot(dd,aes(x=change,y=industry,
colour=geo))+
geom_point(size=2)+
geom_segment(aes(xend=0,yend=industry))
You might want to consider manually dodging the position in the second case, but position_dodge in ggplot can only dodge horizontally, so you should either switch x and y and use coord_flip(), or use position_dodgev from the ggstance package.
I use ggplot2::ggplot for all 2D plotting needs, including density plots, but I find that when plotting a number of overlapping densities with extreme outliers on a single space (in different colors) the line on the x-axis becomes a little distracting.
My question is then, can you remove the bottom section of the density plot from being plotted? If so, how?
You can use this example:
library(ggplot2)
ggplot(movies, aes(x = rating)) + geom_density()
Should turn out like this:
How about using stat_density directly
ggplot(movies, aes(x = rating)) + stat_density(geom="line")
You can just draw a white line over it:
ggplot(movies, aes(x = rating)) +
geom_density() +
geom_hline(color = "white", yintercept = 0)
Adding a secondary y axis, scaled one of the original y axis. This topic is not new. It has been touched times, for example on this ggplot2 google groups thread. Following Hadley's advice, I tried to add the secondary y axis by geom_vline, geom_segment, and geom_text. But, it is still ugly.
So I would ask for your help on making it perfect. I think many ggplot2 users would be interested in this topic and prefer any your expertise or contributions. Thanks in advance.
#########################################
# what I have gotten.
library(ggplot2)
# build up a box plot
p <- ggplot(mtcars, aes(factor(cyl), mpg))
# add the secondary y axis on right side of the plot
p + geom_boxplot() + geom_vline(xintercept = 3.5) +
geom_segment(aes(x=3.49, y=c(7,14,21,28), xend = 3.52, yend = c(7,14,21,28))) +
geom_text(aes(x=3.55, y=c(7,14,21,28), label=c(7,14,21,28)))
To avoid hacking, you might use facet_grid instead. Depending on your data, you can customize it pretty well, to make it into more general secondary axis.
library(ggplot2)
ggplot(mtcars, aes(factor(cyl), mpg)) +
geom_boxplot() +
facet_grid(cyl ~., scales = "free")