Showing median value in grouped boxplot in R

Question

I have created boxplots using ggplot2 with this code.

plotgraph <- function(x, y, colour, min, max)
{
    plot1 <- ggplot(dims, aes(x = x, y = y, fill = Region)) +
        geom_boxplot()
    #plot1 <- plot1 + scale_x_discrete(name = "Blog Type")
    plot1 <- plot1 + labs(color='Region') + geom_hline(yintercept = 0, alpha = 0.4)
    plot1 <- plot1 + scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max))
    plot1 <- plot1 + labs(x="Blog Type", y="Dimension Score") + scale_fill_grey(start = 0.3, end = 0.7) + theme_grey()
    plot1 <- plot1 + theme(legend.justification = c(1, 1), legend.position = c(1, 1))
    return(plot1)
}
plot1 <- plotgraph (Blog, Dim1, Region, -30, 25)

A part of data I use is reproduced here.

Blog,Region,Dim1,Dim2,Dim3,Dim4
BlogsInd.,PK,-4.75,13.47,8.47,-1.29
BlogsInd.,PK,-5.69,6.08,1.51,-1.65
BlogsInd.,PK,-0.27,6.09,0.03,1.65
BlogsInd.,PK,-2.76,7.35,5.62,3.13
BlogsInd.,PK,-8.24,12.75,3.71,3.78
BlogsInd.,PK,-12.51,9.95,2.01,0.21
BlogsInd.,PK,-1.28,7.46,7.56,2.16
BlogsInd.,PK,0.95,13.63,3.01,3.35
BlogsNews,PK,-5.96,12.3,6.5,1.49
BlogsNews,PK,-8.81,7.47,4.76,1.98
BlogsNews,PK,-8.46,8.24,-1.07,5.09
BlogsNews,PK,-6.15,0.9,-3.09,4.94
BlogsNews,PK,-13.98,10.6,4.75,1.26
BlogsNews,PK,-16.43,14.49,4.08,9.91
BlogsNews,PK,-4.09,9.88,-2.79,5.58
BlogsNews,PK,-11.06,16.21,4.27,8.66
BlogsNews,PK,-9.04,6.63,-0.18,5.95
BlogsNews,PK,-8.56,7.7,0.71,4.69
BlogsNews,PK,-8.13,7.26,-1.13,0.26
BlogsNews,PK,-14.46,-1.34,-1.17,14.57
BlogsNews,PK,-4.21,2.18,3.79,1.26
BlogsNews,PK,-4.96,-2.99,3.39,2.47
BlogsNews,PK,-5.48,0.65,5.31,6.08
BlogsNews,PK,-4.53,-2.95,-7.79,-0.81
BlogsNews,PK,6.31,-9.89,-5.78,-5.13
BlogsTech,PK,-11.16,8.72,-5.53,8.86
BlogsTech,PK,-1.27,5.56,-3.92,-2.72
BlogsTech,PK,-11.49,0.26,-1.48,7.09
BlogsTech,PK,-0.9,-1.2,-2.03,-7.02
BlogsTech,PK,-12.27,-0.07,5.04,8.8
BlogsTech,PK,6.85,1.27,-11.95,-10.79
BlogsTech,PK,-5.21,-0.89,-6,-2.4
BlogsTech,PK,-1.06,-4.8,-8.62,-2.42
BlogsTech,PK,-2.6,-4.58,-2.07,-3.25
BlogsTech,PK,-0.95,2,-2.2,-3.46
BlogsTech,PK,-0.82,7.94,-4.95,-5.63
BlogsTech,PK,-7.65,-5.59,-3.28,-0.54
BlogsTech,PK,0.64,-1.65,-2.36,-2.68
BlogsTech,PK,-2.25,-3,-3.92,-4.87
BlogsTech,PK,-1.58,-1.42,-0.38,-5.15
Columns,PK,-5.73,3.26,0.81,-0.55
Columns,PK,0.37,-0.37,-0.28,-1.56
Columns,PK,-5.46,-4.28,2.61,1.29
Columns,PK,-3.48,2.38,12.87,3.73
Columns,PK,0.88,-2.24,-1.74,3.65
Columns,PK,-2.11,4.51,8.95,2.47
Columns,PK,-10.13,10.73,9.47,-0.47
Columns,PK,-2.08,1.04,0.11,0.6
Columns,PK,-4.33,5.65,2,-0.77
Columns,PK,1.09,-0.24,-0.92,-0.17
Columns,PK,-4.23,-4.01,-2.32,6.26
Columns,PK,-1.46,-1.53,9.83,5.73
Columns,PK,9.37,-1.32,1.27,-4.12
Columns,PK,5.84,-2.42,-5.21,1.07
Columns,PK,8.21,-9.36,-5.87,-3.21
Columns,PK,7.34,-7.3,-2.94,-5.86
Columns,PK,1.83,-2.77,1.47,-4.02
BlogsInd.,PK,14.39,-0.55,-5.42,-4.7
BlogsInd.,US,22.02,-1.39,2.5,-3.12
BlogsInd.,US,4.83,-3.58,5.34,9.22
BlogsInd.,US,-3.24,2.83,-5.3,-2.07
BlogsInd.,US,-5.69,15.17,-14.27,-1.62
BlogsInd.,US,-22.92,4.1,5.79,-3.88
BlogsNews,US,0.41,-2.03,-6.5,2.81
BlogsNews,US,-4.42,8.49,-8.04,2.04
BlogsNews,US,-10.72,-4.3,3.75,11.74
BlogsNews,US,-11.29,2.01,0.67,8.9
BlogsNews,US,-2.89,0.08,-1.59,7.06
BlogsNews,US,-7.59,8.51,3.02,12.33
BlogsNews,US,-7.45,23.51,2.79,0.48
BlogsNews,US,-12.49,15.79,-9.86,18.29
BlogsTech,US,-11.59,6.38,11.79,-7.28
BlogsTech,US,-4.6,4.12,7.46,3.36
BlogsTech,US,-22.83,2.54,10.7,5.09
BlogsTech,US,-4.83,3.37,-8.12,-0.9
BlogsTech,US,-14.76,29.21,6.23,9.33
Columns,US,-15.93,12.85,19.47,-0.88
Columns,US,-2.78,-1.52,8.16,0.24
Columns,US,-16.39,13.08,11.07,7.56

Even though I have tried to add detailed scale on y-axis, it is hard for me to pinpoint exact median score for each boxplot. So I need to print median value within each boxplot. There was another answer available (for faceted boxplot) which does not work for me as the printed values are not within the boxes but jammed together in the middle. It will be great to be able to print them within (middle and above the median line of) boxplots. Thanks for your help. Edit: I make a grouped graph as below. Add

Haboryme · Accepted Answer · 2017-01-29T10:49:53.680

4

library(dplyr)
dims=dims%>%
  group_by(Blog,Region)%>%
  mutate(med=median(Dim1))
plotgraph <- function(x, y, colour, min, max)
{
  plot1 <- ggplot(dims, aes(x = x, y = y, fill = Region)) +
    geom_boxplot()+
    labs(color='Region') + 
    geom_hline(yintercept = 0, alpha = 0.4)+
    scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max))+
    labs(x="Blog Type", y="Dimension Score") + scale_fill_grey(start = 0.3, end = 0.7) + 
    theme_grey()+
    theme(legend.justification = c(1, 1), legend.position = c(1, 1))+
    geom_text(aes(y = med,x=x, label = round(med,2)),position=position_dodge(width = 0.8),size = 3, vjust = -0.5,colour="blue")
  return(plot1)
}
plot1 <- plotgraph (Blog, Dim1, Region, -30, 25)

Which gives (the text colour can be tweaked to something less tacky):

Note: You should consider using non-standard evaluation in your function rather than having it require the use of attach()

Edit:
One liner, not as clean I wanted it to be since I ran into problems with dplyr not properly aggregating the data even though it says the grouping was performed. This function assume the dataframe is always called dims

library(ggplot2)
library(reshape2)
plotgraph <- function(x, y, colour, min, max)
{
  plot1 <- ggplot(dims, aes_string(x = x, y = y, fill = colour)) +
    geom_boxplot()+
    labs(color=colour) + 
    geom_hline(yintercept = 0, alpha = 0.4)+
    scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max))+
    labs(x="Blog Type", y="Dimension Score") +
    scale_fill_grey(start = 0.3, end = 0.7) + 
    theme_grey()+
    theme(legend.justification = c(1, 1), legend.position = c(1, 1))+
    geom_text(data= melt(with(dims, tapply(eval(parse(text=y)),list(eval(parse(text=x)),eval(parse(text=colour))), median)),varnames=c("Blog","Region"),value.name="med"),
              aes_string(y = "med",x=x, label = "med"),position=position_dodge(width = 0.8),size = 3, vjust = -0.5,colour="blue")
  return(plot1)
}
plot1 <- plotgraph ("Blog", "Dim1", "Region", -30, 25)

edited Jan 29 '17 at 10:49

answered Jan 28 '17 at 20:52

Haboryme

4,611
2
18
21

Thanks. Since I pass on my variables. Using parts of attached variables instead of passed on variables (x, y) is required to make this code re-useable (I create 4 graphs simultaneously). Perhaps you referred to the same non-standard evaluation. I am currently trying to learn and understand what does this term mean. – Shakir Jan 28 '17 at 21:22
[NSE](https://cran.r-project.org/web/packages/dplyr/vignettes/nse.html) This would mean using `aes_string` for the ggplot function and `mutate_` in the dplyr function that creates the dataframe if we were to make it really functional. – Haboryme Jan 28 '17 at 21:28
So I have put the dplyr code in the function `dims <- read.csv("") attach(dims) summary(dims) dims=dims%>% group_by_(x,colour)%>% mutate_(med=median(y))` Adding respective string functions. Similarly both aes functions are also _string: `plot1 <- ggplot(dims, aes_string(x = x, y = y, fill = colour)) + geom_boxplot()` and – Shakir Jan 29 '17 at 09:41
`geom_text(aes_string(y = med,x=x, label = round(med,2)),position=position_dodge(width = 0.8),size = 3, vjust = -0.5,colour="blue")` but there is something wrong definitely. – Shakir Jan 29 '17 at 09:44
1

I combined it in a single function. It works for me. – Haboryme Jan 29 '17 at 10:51
Thanks a lot. There were errors with dplyr like object 'med' not found while it was there in the data frame when I listed it. Anyways now I will try to learn something about reshape2 as well. – Shakir Jan 29 '17 at 11:48
1

@MuhammadShakirAziz: I don't use `dplyr` in the function anymore because I had some unforeseen issues with NSE with it. With reshape2 (it simply an easy way of turning a wide format into a long format) I circumvented these issues. – Haboryme Jan 29 '17 at 11:58
Yeah I understood it. I want to add `round()` for `mean` (by replacing `median` in `geom_text`. Where should this be added? – Shakir Jan 29 '17 at 12:44
@MuhammadShakirAziz : in `geom_text`you can replace "med" from `label' with "round(med,2)" to have the rouding. If you want `mean` instead of `median` you can change `median` (inside the `melt()`) to another function. Note that the variable would still be called "med". – Haboryme Jan 29 '17 at 12:49
can you please take a look at my question? https://stackoverflow.com/questions/65547448/r-for-the-same-code-labels-q1-median-appear-on-one-computer-but-dont-appea thanks – stats_noob Jan 04 '21 at 21:56

score 2 · Answer 2 · answered Jan 28 '17 at 20:51

2

Assuming that Blog is your dataframe, the following should work:

min <- -30 
max <- 25
meds <- aggregate(Dim1~Region, Blog, median)
plot1 <- ggplot(Blog, aes(x = Region, y = Dim1, fill = Region)) +
  geom_boxplot()
plot1 <- plot1 + labs(color='Region') + geom_hline(yintercept = 0, alpha = 0.4)
plot1 <- plot1 + scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max))
plot1 <- plot1 + labs(x="Blog Type", y="Dimension Score") + scale_fill_grey(start = 0.3, end = 0.7) + theme_grey()
plot1 + theme(legend.justification = c(1, 1), legend.position = c(1, 1)) +
  geom_text(data = meds, aes(y = Dim1, label = round(Dim1,2)),size = 5, vjust = -0.5, color='white')

answered Jan 28 '17 at 20:51

Sandipan Dey

21,482
2
51
63

Thanks. My dataframe is dims object that I attach before this function and then pass one different variables from it to create a number of plots simultaneously. – Shakir Jan 28 '17 at 21:20
then you need to use `aes_string`, i guess `aes` will not work. – Sandipan Dey Jan 28 '17 at 21:21
can you please take a look at my question? https://stackoverflow.com/questions/65547448/r-for-the-same-code-labels-q1-median-appear-on-one-computer-but-dont-appea thanks – stats_noob Jan 04 '21 at 21:56

Showing median value in grouped boxplot in R

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