Increase spaces between x values of boxplot (overlapping x labels) - r

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)

Related

Plot on reciprocity scale in R

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())

Introduce explicit line break in ggplot2 on the Y-axis (boxplot)

I'm attempting to write some code that can be used to make boxplots of temperatures at which proteins melt at, I'm 99% there except I need to introduce a line break on the y-axis of my boxplot.
Essentially, my current y axis scale goes from 45-60, I want to make the y axis start at 0, line break, 45-60. See the picture as an e.g.
I've tried using the scale_y_continuous to set a break but that didn't work as I'd hoped.
df %>%
group_by(Protein) %>%
ggplot(., aes(x = factor(Protein), y = Melting_Temperature)) +
geom_boxplot() +
theme_classic() +
geom_point(aes(x = as.numeric(df$Protein) + 0.5, colour = Protein),
alpha=0.7)+
xlab("Protein Type")+
ylab("Melting Temperature") +
stat_summary(fun.y=mean, colour = "darkred", geom = "point", shape =
18, size = 3, show_guide = FALSE) +
geom_text(data = means, aes(label = round(Melting_Temperature, 1), y =
Melting_Temperature + 0.5))
IMHO, tick marks and axis labels should be sufficient to indicate the range of data on display. So, there is no need to start an axis at 0 (except for bar charts and alike).
However, the package ggthemes offers Tufte style axes which might be an alternative to the solution the OP is asking for:
library(ggplot2)
library(ggthemes)
ggplot(iris) +
aes(x = Species, y = Sepal.Length) +
geom_boxplot() +
geom_rangeframe() +
theme_tufte(base_family = "")
Note that the iris dataset is used here in place of OP's data which are not available.
geom_rangeframe() plots axis lines which extend to the maximum and minimum of the plotted data. As the plot area is usually somewhat larger this creates a kind of gap.
theme_tufte() is a theme based on Chapter 6 "Data-Ink Maximization and Graphical Design" of Edward Tufte's The Visual Display of Quantitative Information with no border, no axis lines, and no grids.
This is not supported in ggplot as built. In this discussion from 2010, Hadley Wickham (author of ggplot as well as RStudio et al) explains that axis breaks are questionable practice in his view.
Those comments by Hadley are linked, and other options discussed, in this prior SO discussion.

No line in plot chart despite + geom_line()

I've read documentation and I think that my code should be right, but still there is no line between the points in the output. What is wrong?
The x'axis is discrete and y'axis is continuous.
My code
point.sqrmPrice <- ggplot(overview.df, aes(x = areaSize, y = sqrmPrice)) +
geom_line() +
geom_point() +
scale_y_continuous(breaks = c(seq(min(overview.df$sqrmPrice), max(overview.df$sqrmPrice), by = 10000) )) +
theme_bw()
The underlying issue here is a duplicate of this stack post.
Here's a reproducible example showing what #SN248 meant about adding group to the code
ggplot(iris, aes(x = factor(Sepal.Length), y = Sepal.Width)) +
geom_line(aes(group=1)) + geom_point() + theme_bw()
You are not getting a line because areaSize is a factor. Convert to numeric with
overview.df$areaSize <- as.numeric(as.character(overview.df$areaSize))
and then make the plot.
What you have to think about it is, do you expect a single line to connect all the dots?
Else, how many lines do you expect, that will tell you how many groups will you need to have.
You are missing the group aesthetic required for geom_line(), because you haven't specified how many groups (lines) you want in your plot.

how to prevent axes from intersecting in ggplot2

I'm using ggplot2 to make line graphs of some log-transformed data that all have large values (between 10^6 and 10^8); since the axes doesn't start at zero, I'd prefer not to have them intersect at the "origin."
Here's what the axes currently look like:
I'd prefer something more like one gets from base graphics (but I'm additionally using geom_ribbon and other fancy things I really like in ggplot2, so I'd prefer to find a ggplot2 solution):
Here's what I'm doing currently:
mydata <- data.frame(Day = rep(1:8, 3),
Treatment = rep(c("A", "B", "C"), each=8),
Value = c(7.415929, 7.200486, 7.040555, 7.096490, 7.056413, 7.143981, 7.429724, 7.332760, 7.643673, 7.303994, 7.343151, 6.923636, 6.923478, 7.249170, 7.513370, 7.438630, 7.209895, 7.000063, 7.160154, 6.677734, 7.026307, 6.830495, 6.863329, 7.319219))
ggplot(mydata, aes(x=Day, y=Value, group=Treatment))
+ theme_classic()
+ geom_line(aes(color = Treatment), size=1)
+ scale_y_continuous(labels = math_format(10^.x))
+ coord_cartesian(ylim = c(6.4, 7.75), xlim=c(0.5, 8))
plot(mydata$Day, mydata$Value, frame.plot = F) #non-intersecting axes
Workaround for this problem would be to remove axis lines with theme(axis.line=element_blank()) and then add false axis lines with geom_segment() - one for x axis and second for y axis. x, y , xend and yend values are determined from your plot (taken as the smallest and the largest values shown on plot for each corresponding axis) and axis limits used in coord_cartesian() (minimal value of limits to ensure that segment is plotted in place of axis).
ggplot(mydata, aes(x=Day, y=Value, group=Treatment)) +theme_classic() +
geom_line(aes(color = Treatment), size=1) +
scale_y_continuous(labels = math_format(10^.x))+
coord_cartesian(ylim = c(6.4, 7.75), xlim=c(0.5, 8))+
theme(axis.line=element_blank())+
geom_segment(x=2,xend=8,y=6.4,yend=6.4)+
geom_segment(x=0.5,xend=0.5,y=6.5,yend=7.75)
An older question. But since I was looking for this functionality recently I thought I'd flag the ggh4x package, which adds guides for truncating axes.
library(ggh4x)
#> Loading required package: ggplot2
ggplot(data.frame(x=0:10, y=0:10), aes(x, y)) +
geom_point() +
theme_classic() +
guides(x = "axis_truncated", y = "axis_truncated")
Created on 2023-02-17 with reprex v2.0.2
Apart from convenience, two nice things about the ggh4x option are that 1) it is stable across more complex plot compositions like faceting and 2) its dependencies are a subset of those belonging to ggplot2, so you aren't introducing a bunch of additional imports.
P.S. There's an open GitHub issue to bring this kind of "floating axes" functionality to the main ggplot2 library. It looks like it will eventually be incorporated.

add a secondary y axis to ggplot2 plots - make it perfect

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")

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