I'm trying to remove the space between the y-axis line and the first tick mark in my plot. Here's an example:
set.seed(201)
n <- 100
dat <- data.frame(xval = (1:n+rnorm(n,sd=5))/20, yval = 2*2^((1:n+rnorm(n,sd=5))/20))
dat[dat[,1] < 0,1] <- 0
dat[dat[,2] < 0,2] <- 0
ggplot(dat, aes(xval, yval)) + geom_point()
This code plots a graphic with a space between the y-axis line and the zero tick mark in the x-axis. How can I remove it?
You can alter this "gap" using the scale_x_continuous function:
ggplot(dat, aes(xval, yval)) + geom_point() +
scale_x_continuous(expand=c(0,0))
From the help file on scale_x_continuous,
expand: numeric vector of length two giving multiplicative and
additive expansion constants. These constants ensure that the data is
placed some distance away from the axes.
To alter the space on the y-axis, use scale_y_continuous
Related
I'm trying to force the grid of a scatter plot to be composed of squares, with x and y values that have different ranges.
I tried to force a square shape of the whole plot (aspect.ratio=1), but this does not solve the problem of different ranges. Then I tried to change limits of values of my axes.
1)Here is what I tried first:
p + theme(aspect.ratio = 1) +
coord_fixed(ratio=1, xlim = c(-0.050,0.050),ylim = c(-0.03,0.03))
2) I changed the ratio by using the range of the values for each axis:
p + coord_fixed(ratio=0.06/0.10, xlim = c(-0.050,0.050), ylim = c(-0.03,0.03))
3)Then I changed the limits of y to match those of x:
p + theme(aspect.ratio = 1) +
coord_fixed(ratio=1, xlim = c(-0.050,0.050),ylim = c(-0.05,0.05))
1) The grid on the background is composed by rectangles.
2) I would expect this to change the position of the tick marks automatically in order to give me a grid composed of squares. Still triangles.
3) It obviously worked 'cause I matched the ranges of x and y. But there was a lot of empty space in the graph.
Is there something else I should try?
Thanks in advance.
If you want the plot to be square and you want the grid to be square you can do this by rescaling the y variable to be on the same scale as the x variable (or vice versa) for plotting, and then inverting the rescaling to generate the correct axis value labels for the rescaled axis.
Here's an example using the mtcars data frame, and we'll use the rescale function from the scales package.
First let's create a plot of mpg vs. hp but with the hp values rescaled to be on the same scale as mpg:
library(tidyverse)
library(scales)
theme_set(theme_bw())
p = mtcars %>%
mutate(hp.scaled = rescale(hp, to=range(mpg))) %>%
ggplot(aes(mpg, hp.scaled)) +
geom_point() +
coord_fixed() +
labs(x="mpg", y="hp")
Now we can invert the rescaling to generate the correct value labels for hp. We do that below by supplying the inverting function to the labels argument of scale_y_continuous:
p + scale_y_continuous(labels=function(x) rescale(x, to=range(mtcars$hp)))
But note that rescaling back to the original hp scale results in non-pretty breaks. We can fix that by generating pretty breaks on the hp scale, rescaling those to the mpg scale to get the locations where we want the tick marks and then inverting that to get the label values. However, in that case we won't get a square grid if we want to keep the overall plot panel square:
p + scale_y_continuous(breaks = rescale(pretty_breaks(n=5)(mtcars$hp),
from=range(mtcars$hp),
to=range(mtcars$mpg)),
labels = function(x) rescale(x, from=range(mtcars$mpg), to=range(mtcars$hp)))
I'm not sure what code you are using, it is missing in block 1 and 3. But using the mtcars data set the following works:
library(ggplot2)
ggplot(mtcars, aes(mpg, wt)) +
geom_point() +
coord_fixed(ratio = 1) +
scale_x_continuous(breaks = seq(10, 35, 1)) +
scale_y_continuous(breaks = seq(1, 6, 1))
The last two lines make it clear that 1 point on the x-axis is equal to 1 point on the y-axis.
In the documention you will further find the following advise:
ensures that the ranges of axes are equal to the specified ratio by
adjusting the plot aspect ratio
This is should be very simple question!
I would like to make a barplot with errorbars and I'm using the following code:
ggplot(data = bars, aes(x=c("1","2","3"), y=V2, fill = names)) +
geom_bar(position=position_dodge(), stat="identity", alpha = 0.7) +
geom_errorbar(aes(ymin=V1, ymax=V3))+
theme(legend.position='none')+
coord_cartesian(ylim=c(0,10))
However, I have 2 problems:
1. I would like the bars to start at y = 0
2. I don't like the ticks in the y axis. I would like numbers with just one decimal and less ticks.
this is my actual plot: Bars with error bars
For the first problem (if I understand it correctly) you can use ylim
... + ylim(0.2, NA)
NA leaves the upper bound free.
For the second, I suggest to use pretty_breaks from scale
library(scales)
... + scale_y_continuous(breaks=pretty_breaks(n=5))
I have some code that is plots a histogram of some values, along with a few horizontal lines to represent reference points to compare against. However, ggplot is not generating a legend for the lines.
library(ggplot2)
library(dplyr)
## Siumlate an equal mix of uniform and non-uniform observations on [0,1]
x <- data.frame(PValue=c(runif(500), rbeta(500, 0.25, 1)))
y <- c(Uniform=1, NullFraction=0.5) %>% data.frame(Line=names(.) %>% factor(levels=unique(.)), Intercept=.)
ggplot(x) +
aes(x=PValue, y=..density..) + geom_histogram(binwidth=0.02) +
geom_hline(aes(yintercept=Intercept, group=Line, color=Line, linetype=Line),
data=y, alpha=0.5)
I even tried reducing the problem to just plotting the lines:
ggplot(y) +
geom_hline(aes(yintercept=Intercept, color=Line)) + xlim(0,1)
and I still don't get a legend. Can anyone explain why my code isn't producing plots with legends?
By default show_guide = FALSE for geom_hline. If you turn this on then the legend will appear. Also, alpha needs to be inside of aes otherwise the colours of the lines will not be plotted properly (on the legend). The code looks like this:
ggplot(x) +
aes(x=PValue, y=..density..) + geom_histogram(binwidth=0.02) +
geom_hline(aes(yintercept=Intercept, colour=Line, linetype=Line, alpha=0.5),
data=y, show_guide=TRUE)
And output:
I am making a plot in ggplot2 where on the y axis I have the indices of groups and on the x axis some information. For readability I would like to make the labels bigger but then they start overlapping. Therefore I would like to put the labels into two columns as shown in the figure so they can be bigger. Is there a way to do this in ggplot? I tried vjust and hjust but they only seem to accept 1 argument applying to all labels.
Current labels:
Objective labeling:
Well, there is no obvious parameter responsible for that, at least AFAIK.
However, for your specific goal my first thought was to add some spaces to numeric labels.
avoid_overlap <- function(x)
{
ind <- seq_along(x) %% 2 == 0
x[ind] <- paste0(x[ind], " ")
x
}
ggplot(mtcars, aes(cyl, mpg)) + geom_point() +
scale_y_continuous(breaks = 10:35, labels = avoid_overlap(10:35)) +
theme(axis.text.y = element_text(size = 32))
Play with grid lines (minor/major) via theme if the grid is too dense.
I have a plot using ggplot, and I would like to add points and error bars to it. I am using geom_errorbar and geom_point, but I am getting an error: "Discrete value supplied to continuous scale" and I am not sure why. The data labels in the plot below should remain the same. I simply want to add new points to the existing graph. The new graph should look like the one below, except with two points/CI bars for each label on the Y axis.
The following example is from the lme4 package, and it produces a plot with confidence intervals using ggplot below (all can be replicated except the last two lines of borken code). My data is only different in that it includes about 15 intercepts instead of 6 below (which is why I am using scale_shape_manual).
The last two lines of code is my attempt at adding points/confidence intervals. I'm going to put a 50 bounty on this. Please let me know if I am being unclear. Thanks!
library("lme4")
data(package = "lme4")
# Dyestuff
# a balanced one-way classiï¬cation of Yield
# from samples produced from six Batches
summary(Dyestuff)
# Batch is an example of a random effect
# Fit 1-way random effects linear model
fit1 <- lmer(Yield ~ 1 + (1|Batch), Dyestuff)
summary(fit1)
coef(fit1) #intercept for each level in Batch
randoms<-ranef(fit1, postVar = TRUE)
qq <- attr(ranef(fit1, postVar = TRUE)[[1]], "postVar")
rand.interc<-randoms$Batch
#THESE ARE THE ADDITIONAL POINTS TO BE ADDED TO THE PLOT
Inter <- c(-25,-45,20,30,23,67)
SE2 <- c(20,20,20,20,20,20)
df<-data.frame(Intercepts=randoms$Batch[,1],
sd.interc=2*sqrt(qq[,,1:length(qq)]), Intercepts2=Inter, sd.iterc2=SE2,
lev.names=rownames(rand.interc))
df$lev.names<-factor(df$lev.names,levels=df$lev.names[order(df$Intercepts)])
library(ggplot2)
p <- ggplot(df,aes(lev.names,Intercepts,shape=lev.names))
#Added horizontal line at y=0
#Includes first set of points/confidence intervals. This works without error
p <- p + geom_hline(yintercept=0) +geom_errorbar(aes(ymin=Intercepts-sd.interc, ymax=Intercepts+sd.interc), width=0,color="black") + geom_point(aes(size=2))
#Removed legends and with scale_shape_manual point shapes set to 1 and 16
p <- p + guides(size=FALSE,shape=FALSE) + scale_shape_manual(values=c(16,16,16,16,16,16))
#Changed appearance of plot (black and white theme) and x and y axis labels
p <- p + theme_bw() + xlab("Levels") + ylab("")
#Final adjustments of plot
p <- p + theme(axis.text.x=element_text(size=rel(1.2)),
axis.title.x=element_text(size=rel(1.3)),
axis.text.y=element_text(size=rel(1.2)),
panel.grid.minor=element_blank(),
panel.grid.major.x=element_blank())
#To put levels on y axis you just need to use coord_flip()
p <- p+ coord_flip()
print(p)
#####
# code for adding more plots, NOT working yet
p <- p +geom_errorbar(aes(ymin=Intercepts2-sd.interc2, ymax=Intercepts2+sd.interc2),
width=0,color="gray40", lty=1, size=1)
p <- p + geom_point(aes(Intercepts2, lev.names),size=0,pch=7)
First, in your data frame df and geom_errorbar() there are two different variables sd.iterc2 and sd.interc2. Changed also in df to sd.interc2.
For the last line of geom_point() you get the error because your x and y values are in wrong order. As your are using coord_flip() then x and y values should be placed in the same order as in original plot before coord_flip(), that is, lev.names as x, and Intercepts2 as y. Changed also size= to 5 for better illustration.
+ geom_point(aes(lev.names,Intercepts2),size=5,pch=7)
Update - adding legend
To add legend for the points of intercept types, one option is to reshape your data to long format and add new column with intercept types. Other option with your existing data is, first, remove shape=lev.names from ggplot() call. Then in both geom_point() calls add shape="somename" inside aes(). Then with scale_shape_manual() set shape values you need.
ggplot(df,aes(lev.names,Intercepts))+
geom_hline(yintercept=0) +
geom_errorbar(aes(ymin=Intercepts-sd.interc, ymax=Intercepts+sd.interc), width=0,color="black")+
geom_point(aes(shape="Intercepts"),size=5)+
theme_bw() + xlab("Levels") + ylab("")+
theme(axis.text.x=element_text(size=rel(1.2)),
axis.title.x=element_text(size=rel(1.3)),
axis.text.y=element_text(size=rel(1.2)),
panel.grid.minor=element_blank(),
panel.grid.major.x=element_blank())+
coord_flip()+
geom_errorbar(aes(ymin=Intercepts2-sd.interc2, ymax=Intercepts2+sd.interc2),
width=0,color="gray40", lty=1, size=1) +
geom_point(aes(lev.names,Intercepts2,shape="Intercepts2"),size=5)+
scale_shape_manual(values=c(16,7))