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I had a question on how to change/customize the upper and lower limit of a notch on a boxplot created by ggplot2. I looked through the function stat_boxplot and found that ggplot calculates the notch limits with the equation median +/- 1.58 * iqr / sqrt(n). However instead of that equation I wanted to change it with my own set of upper and lower notch limits.
My data has 4 factors and for each factor I calculated the median and did a bootstrap to get a 95% confidence interval of that median. Thus in the end I would like to change every boxplot to have its own unique notch upper and lower limit.
I'm not sure if this is even possible in ggplot and was wondering if people have an idea on how to do this?
Thanks again!
I've figured out one way to customize the notches on a plot using ggplot with the function ggplot_build.
After plotting a boxplot with say:
p<-ggplot(combined,aes(x=foo,y=bar)) + geom_boxplot(notch=TRUE)
not really sure what exactly happens with ggplot_build but seems like it converts the plot into a data-frame ish structure so one can manipulate it if wanted.
gg<-ggplot_build(p)
afterwards:
gg$data[[1]]$notchlower
gg$data[[1]]$notchupper
contains the notch limits for your plot and you can basically change it with something like:
gg$data[[1]]$notchlower<-50
gg$data[[1]]$notchupper<-100
And if you had mulitple boxplots and wanted to individually change each boxplot:
gg$data[[1]]$notchlower[1]<-50
gg$data[[1]]$notchlower[2]<-50
....
gg$data[[1]]$notchlower[n]<-50
gg$data[[1]]$notchupper[1]<-100
gg$data[[1]]$notchupper[2]<-100
....
gg$data[[1]]$notchupper[n]<-100
Anyways hopefully this is a valid method to do and it would be of help for other people.
Related
This question already has answers here:
geom_bar bars not displaying when specifying ylim
(4 answers)
Closed 9 months ago.
I am trying to create a barplot using ggplot2, with the y axis starting at a value greater than zero.
Lets say I have the means and standard errors for hypothetical dataset about carrot length at three different farms:
carrots<-NULL
carrots$Mean<-c(270,250,240)
carrots$SE<-c(3,4,5)
carrots$Farm<-c("Plains","Hill","Valley")
carrots<-data.frame(carrots)
I create a basic plot:
p<-ggplot(carrots,aes(y=Mean,x=Farm)) +
geom_bar(fill="slateblue") +
geom_errorbar(aes(ymin=Mean-SE,ymax=Mean+SE), width=0)
p
This is nice, but as the scale runs from 0 to it is difficult to see the differences in length. Therefore, I would like to rescale the y axis to something like c(200,300). However, when I try to do this with:
p+scale_y_continuous('Length (mm)', limit=c(200,300))
The bars disappear, although the error bars remain.
My question is: is it possible to plot a barplot with this adjusted axis using ggplot2?
Thank you for any help or suggestions you can offer.
Try this
p + coord_cartesian(ylim=c(200,300))
Setting the limits on the coordinate system performs a visual zoom;
the data is unchanged, and we just view a small portion of the original plot.
If someone is trying to accomplish the same zoom effect for a flipped bar chart, the accepted answer won't work (even though the answer is perfect for the example in the question).
The solution for the flipped bar chart is using the argument ylim of the coord_flip function. I decided to post this answer because my bars were also "disappearing" as in the original question while I was trying to re-scale with other methods, but in my case the chart was a flipped one. This may probably help other people with the same issue.
This is the adapted code, based on the example of the question:
ggplot(carrots,aes(y=Mean,x=Farm)) +
geom_col(fill="slateblue") +
geom_errorbar(aes(ymin=Mean-SE,ymax=Mean+SE), width=0) +
coord_flip(ylim=c(200,300))
Flipped chart example
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is there a way to increase the y axis length to the maximun value?
When I use this code:
par(mfrow=c(3,5))
for (i in c("mrts","p100e10","p75","PIA","pop1076","pop1616","pop2911","pop500","pop800","rev84","SugarCaneFarms","Swiss","USbanks","UScities","UScolleges"))
{
boxplot(dados[[i]],xlab=i)
}
But then it appears boxplots with a low y axis. I need to change the y axis but I didnt want to change one by one, I want to appear the last value.
Boxplots
How Can I do that?
If it is not possible, how can I do it one by one?
Thanks
You can specify ylim with the minimal and maximal values of the y axis.
In your example:
boxplot(dados[[i]],xlab=i,ylim=c(min(dados[[i]]),max(dados[[i]])))
ylim=c(-min,max)
It's a corollary of xlim and should solve your issue.
This question already has answers here:
Using ggplot2, can I insert a break in the axis?
(10 answers)
Closed 3 years ago.
I have used Thinkcell, and one of its cool features is that it breaks very long y-axis to fit the graph. I am not sure whether we can do this with ggplot2. I am a beginner in ggplot2. So, I'd appreciate any thoughts.
For example:
Series <- c(1:6)
Values <- c(899, 543, 787, 35323, 121, 234)
df_val_break <- data.frame(Series, Values)
ggplot(data=df_val_break, aes(x=Series, y=Values)) +
geom_bar(stat="identity")
This creates a graph like this:
However, I want a graph that looks something like this:
However, it seems that broken axis is not supported in ggplot2 because it's misleading (Source: Using ggplot2, can I insert a break in the axis?). This thread suggests a couple of things--faceting and tables.
While I like tables, but I don't like faceting because my categorical variable "Series" are closely related. Moreover, I'd prefer Excel for drawing tables--it's fast.
I have two questions:
Question 1: One of the options I liked is at https://stats.stackexchange.com/questions/1764/what-are-alternatives-to-broken-axes. The graph is at
.
I am unable to replicate similar graph because of the scaling issue.
Question 2: This is a minor question just in case there were new packages introduced that might help us to do this. (The linked SO thread above is older than 5 years. ) Are there any other options on the table?
Update: I don't think my question is duplicate for two reasons: a) I have already gone through the indicated thread, and have referenced here explaining that I am looking for a solution that looks like the third graph in my post. Specifically, I am looking to plot both the graphs--one with shorter scales and the other with 1/20 scale in one graph. I am unable to do this using ggplot2 because of scale issue. Either both the sub-graphs get scaled to 1/nth or one of them get scaled to normal range. I believe this version is much relatable for non-technical audience who don't understand log and Inverse transformation.
I took a stab at this one. I'm a beginner so I am not sure whether this can be improved further in terms of placement of text. I struggled with fitting both high growth rate series and low growth rate series in one graph because of different scales. So, I used facetting.
Here's the code:
ggplot(data = df_val_break,aes(x=Series,y=Values)) +
geom_bar(stat = "identity") +
facet_wrap(~Modified) +
geom_text(data = df_val_break[df_val_break$Modified=="HIGH_GROWTH",], aes(label = "x20 growth rate"),hjust=0.5, vjust=0)
ggsave("post.png")
Here's the output:
There are quite a few issues that I see:
a) High_growth rate graph has Series 2 and Series 6 on the x-axis, although we don't need them. I don't know how to turn them off.
b) geom_text overlaps with the bar. This looks a little annoying.
c) I'd believe that the graph is a little misleading, especially for HIGH_GROWTH section because the y-axis isn't scaled with LOW_GROWTH I was originally thinking of showing two different y-axis--one scaled by 1/20 and the other unscaled.
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I plot two hexbin graphs with R (with package 'hexbin') from data file with two columns gr and ug.
The first plot : gr as a function of ug
The second plot : ug as a fonction of gr
Why aren't they perfectly symmetrical?
Thanks in advance
Notice that in both cases the hexagons are oriented to have 2 sides vertical and no sides horizontal. To be perfectly symmetric one of the plots would need to have the rotated hexagons (2 sides horizontal).
So the binning is slightly different between the 2 graphs and points that are near the boundary in the 1st plot may fall into a different cell (symmetrically) in the 2nd plot. So while the 2 plots are similar overall you will see some minor differences due to how the data is binned.
This is true in general for plots/techniques that depend on binning continuous data, a slight change to how the binning is done will results in usually minor changes in the results. It is good to do multiple plots with small changes to the options that determine the binning to see how much things change.
I just started using ggplot2 on R and have a violin plot question.
I have a data set that can be accessed here: data.
The data comes from a study of making estimations. The variables of interest are the question.no (questions), condition, estimate.no (tr.est1 or tr.est2) and estimate.
The code below makes the plot look almost the way I want it to look at least for one question, yet the median dots generated by stat_summary() are displayed in between the "violins."
v.data<-read.csv("data.csv")
# loop through each question number
d_ply(v.data, c("question.no"), function(d.plot){
q.no <- v.data$question.no
plot.q <- ggplot(d.plot,aes(condition, estimate, fill=estimate.no)) +
geom_violin() +
stat_summary(fun.y="median", geom="point") +
scale_y_continuous('Change Scores') +
scale_x_discrete("Conditions")
ggsave(filename=paste(q.no,".png",sep=""))
})
My Question: How can I make the median dots display correctly on the "violins" rather than in between them?
I searched the previous questions asked on ggplot2 on this site and looked at the ggplot2 documentation as well as other R forums but have not been able to find anything relevant.
I would appreciate any comments and suggestions as to how I can fix it. Also, if the questions I ask are already answered somewhere else, I would appreciate the links to the threads,too. Many thanks in advance.
stat_summary is limited to the variable that determines your x-axis. One way to convey the information you want would be to replace condition in your call to aes with interaction(condition, estimate.no).
Plotluck is a library based on ggplot2 that aims at automating the choice of plot type based on characteristics of 1-3 variables. For your data set, the command plotluck(v.data, condition, estimate, question.no) generates the following plot:
Note that the library chose to scale y logarithmically. You can override this behavior with plotluck(v.data,condition,estimate,question.no,opts=plotluck.options(trans.log.thresh=1E20)) but it doesn't display well, and the median points look like they are all on the zero line.