I have produced the graph pictured using the following code -
ggboxplot(xray50g, x = "SupplyingSite", y = "PercentPopAff",
fill = "SupplyingSite", legend = "none") +
geom_point() +
rotate_x_text(angle = 45) +
# ADD HORIZONTAL LINE AT BASE MEAN
geom_hline(yintercept = mean(xray50g$PercentPopAff), linetype = 2)
What I would like to do is label the horizontal geom_hline with it's numeric value so that it appears on the y axis.
I have provided an example of what I would like to achieve in the second image.
Could somebody please help with the code to achieve this for my plot?
Thanks!
There's a really great answer that should help you out posted here. As long as you are okay with formatting the "extra tick" to match the existing axis, the easiest solution is to just create your axis breaks manually and specify within scale_y_continuous. See below where I use an example to label a vertical dotted line on the x-axis using this method.
df <- data.frame(x=rnorm(1000, mean = 0.5))
ggplot(df, aes(x)) +
geom_histogram(binwidth = 0.1) +
geom_vline(xintercept = 0.5, linetype=2) +
scale_x_continuous(breaks=c(seq(from=-4,to=4,by=2), 0.5))
Again, for other methods, including those where you want the extra tick mark formatted differently than the rest of the axis, check the top answer here.
Related
I have been trying to add a bell curve to my histogram an outline it with a color so that it is more pleasing. enter image description here
I have added what my histogram looks like to give someone an idea on what I am working with, also here is my code thus far, thank you in advance.
ggplot(data = mammal.data.22.select2)+
geom_histogram(aes(x=Time, fill=Species))+
scale_fill_manual(values=c("paleturquoise4", "turquoise2"))+
facet_wrap(~Species, nrow=1)+
ylab("Observations")+
xlab("Time of Day")+
theme(strip.text.x = element_blank())
Let's build a histogram with a build-in dataset that seems similar-ish to your data structure.
library(ggplot2)
binwidth <- 0.25
p <- ggplot(iris, aes(Petal.Length)) +
geom_histogram(
aes(fill = Species),
binwidth = binwidth,
alpha = 0.5
) +
facet_wrap(~ Species)
You can use stat_bin() + geom_step() to give an outline to the histogram, without colouring the edge of every rectangle in the histogram. The only downside is that the first and last bins don't touch the x-axis.
p + stat_bin(
geom = "step", direction = "mid",
aes(colour = Species), binwidth = binwidth
)
To overlay a density function with a histogram, you could calculate the relevant parameters yourself and use stat_function() with fun = dnorm repeatedly. Alternatively, you can use ggh4x::stat_theodensity() to achieve a similar thing. Note that whether you use stat_function() or stat_theodensity(), you should scale the density back to the counts that your histogram uses (or scale histogram to density). In the example below, we do that by using after_stat(count * binwidth).
p + ggh4x::stat_theodensity(
aes(colour = Species,
y = after_stat(count * binwidth))
)
Created on 2022-04-15 by the reprex package (v2.0.1)
(disclaimer: I'm the author of ggh4x)
I'm working now in a statistics project and recently started with R. I have some problems with the visualization. I found a lot of different tutorials about how to add percentage labels in pie charts, but after one hour of trying I still don't get it. Maybe something is different with my data frame so that this doesn't work?
It's a data frame with collected survey answers, so I'm not allowed to publish them here. The column in question (geschäftliche_lage) is a factor with three levels ("Gut", "Befriedigend", "Schlecht"). I want to add percentage labels for each level.
I used the following code in order to create the pie chart:
dataset %>%
ggplot(aes(x= "", fill = geschäftliche_lage)) +
geom_bar(stat= "count", width = 1, color = "white") +
coord_polar("y", start = 0, direction = -1) +
scale_fill_manual(values = c("#00BA38", "#619CFF", "#F8766D")) +
theme_void()
This code gives me the desired pie chart, but without percentage labels. As soon as a I try to add percentage labels, everything is messed up. Do you know a clean code for adding percentage labels?
If you need more information or data, just let me know!
Greetings
Using mtcars as example data. Maybe this what your are looking for:
library(ggplot2)
ggplot(mtcars, aes(x = "", fill = factor(cyl))) +
geom_bar(stat= "count", width = 1, color = "white") +
geom_text(aes(label = scales::percent(..count.. / sum(..count..))), stat = "count", position = position_stack(vjust = .5)) +
coord_polar("y", start = 0, direction = -1) +
scale_fill_manual(values = c("#00BA38", "#619CFF", "#F8766D")) +
theme_void()
Created on 2020-05-25 by the reprex package (v0.3.0)
I've been building a bar graph in R, and I noticed a problem. whenever the graph is made, it has a very small gap between the bars and the axis that causes a line of the background image to appear (Link). How can I get rid of this?
Code:
album_cover <- image_read("https://i.scdn.co/image/ab67616d0000b273922a12ba0b5a66f034dc9959")
ggplot(data=album_df, aes(x=rev(factor(track_names, track_names)), y=-1 * track_length)) +
ggtitle("Songs vs length")+
annotation_custom(rasterGrob(album_cover,
width = unit(1,"npc"),
height = unit(1,"npc")),
-Inf, Inf, -Inf, Inf)+
#geom_image(image = "https://i.scdn.co/image/ab67616d0000b273922a12ba0b5a66f034dc9959", size = Inf) +
geom_bar(stat="identity", position = "identity", color = 'NA', alpha = 0.9, width = 1, fill = 'white') +
scale_y_continuous(expand = c(0, 0), limits = c(-1 * max_track, 0)) +
scale_x_discrete(expand = c(0, 0)) +
theme(axis.title.x=element_blank(),
axis.title.y=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank()
) +
coord_flip()
Interesting issue. I've tried many things, including modification of many of the theme elements. It works with theme_void(), but then the issue resurfaces as you add back in the plot elements (namely the song titles on the axis, for some reason).
What finally did work is just squishing your image to be ever so slightly less than 1. In this case, just changing from 1 to 0.999 fixes the issue and you no longer have the strip of the image hanging out on the right. For this, I made up my own data, but I'm using the same image:
df <- data.frame(
track_names=paste0('Song',1:8),
track_length=c(3.5,7.5,5,3,7,10,6,7.4)
)
album_cover <- image_read2("https://i.scdn.co/image/ab67616d0000b273922a12ba0b5a66f034dc9959")
ggplot(data=df, aes(x=track_names, y=-1*track_length)) +
annotation_custom(rasterGrob(album_cover,
width=unit(0.999,'npc'), height=unit(1,'npc')),
xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) +
geom_col(alpha=0.9, width=1, fill='white', color=NA) +
scale_y_continuous(expand=c(0,0)) +
scale_x_discrete(expand=c(0,0)) +
ggtitle('Songs vs Length') +
coord_flip()
Note, the same code above gives the following image below when width=unit(1, 'npc'),... in the rasterGrob() function (note the line at the right side of the image):
I have a ggplot in which I am using color for my geom_points as a function of one of my columns(my treatment) and then I am using the scale_color_manual to choose the colors.
I automatically get my legend right
The problem is I need to graph some horizontal lines that have to do with the experimental set up, which I am doing with geom_vline, but then I don't know how to manually add a separate legend that doesn't mess with the one I already have and that states what those lines are.
I have the following code
ggplot(dcons.summary, aes(x = meters, y = ymean, color = treatment, shape = treatment)) +
geom_point(size = 4) +
geom_errorbar(aes(ymin = ymin, ymax = ymax)) +
scale_color_manual(values=c("navy","seagreen3"))+
theme_classic() +
geom_vline(xintercept = c(0.23,3.23, 6.23,9.23), color= "bisque3", size=0.4) +
scale_x_continuous(limits = c(-5, 25)) +
labs(title= "Sediment erosion", subtitle= "-5 -> 25 meters; standard deviation; consistent measurements BESE & Control", x= "distance (meters)", y="erosion (cm)", color="Treatment", shape="Treatment")
So I would just need an extra legend beneath the "treatment" one that says "BESE PLOTS LOCATION" and that is related to the gray lines
I have been searching for a solution, I've tried using "scale_linetype_manual" and also "guides", but I'm not getting there
As you provided no reproducible example, I used data from the mtcars dataset.
In addition I modified this similar answer a little bit. As you already specified the color and in addition the fill factor is not working here, you can use the linetype as a second parameter within aes wich can be shown in the legend:
xid <- data.frame(xintercept = c(15,20,30), lty=factor(1))
mtcars %>%
ggplot(aes(mpg ,cyl, col=factor(gear))) +
geom_point() +
geom_vline(data=xid, aes(xintercept=xintercept, lty=lty) , col = "red", size=0.4) +
scale_linetype_manual(values = 1, name="",label="BESE PLOTS LOCATION")
Or without the second data.frame:
ggplot() +
geom_point(data = mtcars,aes(mpg ,cyl, col=factor(gear))) +
geom_vline(aes(xintercept=c(15,20,30), lty=factor(1) ), col = "red", size=0.4)+
scale_linetype_manual(values = 1, name="",label="BESE PLOTS LOCATION")
I am trying to plot two columns of raw data (I have used melt to combine them into one data frame) and then add separate error bars for each. However, I want to make the raw data for each column one pair of colors and the error bars another set of colors, but I can't seem to get it to work. The plot I am getting is at the link below. I want to have different color pairs for the raw data and for the error bars. A simple reproducible example is coded below, for illustrative purposes.
dat2.m<-data.frame(obs=c(2,4,6,8,12,16,2,4,6),variable=c("raw","raw","raw","ip","raw","ip","raw","ip","ip"),value=runif(9,0,10))
c <- ggplot(dat2.m, aes(x=obs, y=value, color=variable,fill=variable,size = 0.02)) +geom_jitter(size=1.25) + scale_colour_manual(values = c("blue","Red"))
c<- c+stat_summary(fun.data="median_hilow",fun.args=(conf.int=0.95),aes(color=variable), position="dodge",geom="errorbar", size=0.5,lty=1)
print(c)
[1]: http://i.stack.imgur.com/A5KHk.jpg
For the record: I think that this is a really, really bad idea. Unless you have a use case where this is crucial, I think you should re-examine your plan.
However, you can get around it by adding a new set of variables, padded with a space at the end. You will want/need to play around with the legends, but this should work (though it is definitely ugly):
dat2.m<- data.frame(obs=c(2,4,6,8,12,16,2,4,6),variable=c("raw","raw","raw","ip","raw","ip","raw","ip","ip"),value=runif(9,0,10))
c <- ggplot(dat2.m, aes(x=obs, y=value, color=variable,fill=variable,size = 0.02)) +geom_jitter(size=1.25) + scale_colour_manual(values = c("blue","Red","green","purple"))
c<- c+stat_summary(fun.data="median_hilow",fun.args=(conf.int=0.95),aes(color=paste(variable," ")), position="dodge",geom="errorbar", size=0.5,lty=1)
print(c)
One way around this would be to use repetitive calls to geom_point and stat_summary. Use the data argument of those functions to feed subsets of your dataset into each call, and set the color attribute outside of aes(). It's repetitive and somewhat defeats the compactness of ggplot, but it'd do.
c <- ggplot(dat2.m, aes(x = obs, y = value, size = 0.02)) +
geom_jitter(data = subset(dat2.m, variable == 'raw'), color = 'blue', size=1.25) +
geom_jitter(data = subset(dat2.m, variable == 'ip'), color = 'red', size=1.25) +
stat_summary(data = subset(dat2.m, variable == 'raw'), fun.data="median_hilow", fun.args=(conf.int=0.95), color = 'pink', position="dodge",geom="errorbar", size=0.5,lty=1) +
stat_summary(data = subset(dat2.m, variable == 'ip'), fun.data="median_hilow", fun.args=(conf.int=0.95), color = 'green', position="dodge",geom="errorbar", size=0.5,lty=1)
print(c)