Box and whisker plots, or just box plots are used for the presentation of continuous data, that can be grouped in categories. The box represent the interquartile range and the horizontal line within it the median value. The whiskers represent the upper and lower adjacent values that lie within 1.5 times the interquartile range (although the definition may very between software programs). Any value outside the whiskers is marked separately as an ‘outlier’.
Download and open the plotbox.rda dataset for this example. The data set contains the maximum flexion in 20 patients before and after a manipulation under anaesthesia. The data can be shown by:
plotbox
Pre Post
1 94 115
2 95 103
3 89 113
4 89 122
5 101 103
6 76 93
7 102 118
8 104 102
9 103 81
10 93 102
11 101 124
12 92 130
13 77 103
14 95 125
15 89 108
16 95 106
17 92 105
18 84 89
19 83 113
20 86 86
To create a box and whisker plot of the pre-mua data:
pre<-ggplot()+geom_boxplot(aes(y=Pre,x=’PreMUA’),data=plotbox)
pre
Add a black and white theme, a title and axes labels:
pre<-pre+theme_bw()+ggtitle(‘Preoperative flexion’)+ylab(label=’max flexion [deg]’)+xlab(label=’Status’)
pre
If you are using ggplot < 0.9.2, the title can be set by:
pre<-pre+ opts(title=’Preoperative flexion’)
pre
To create a similar box and whisker plot of the post-mua flexion:
post<-ggplot()+geom_boxplot(aes(y=Post,x=’PostMUA’),data=plotbox)+theme_bw()+ggtitle(‘Postoperative flexion’)+ylab(label=’max flexion [deg]’)+xlab(label=’Status’)
post
If you are using ggplot < 0.9.2, the title can be set by:
post<-ggplot()+geom_boxplot(aes(y=Post,x=’PostMUA’),data=plotbox)+theme_bw()+opts(title=’Postoperative flexion’)+ylab(label=’max flexion [deg]’)+xlab(label=’Status’)
post
The preMUA plot looks symmetrical with the median in the middle of the box. However, the postMUA plot is clearly skewed as the median is located in the lower part of the box (right skewed, because the tail is to the ‘right’ or higher values). This is also reflected in the descriptive statistics:
descriptive.table(vars = d(Pre,Post),data= plotbox,
+ func.names =c(“Mean”,”Median”))
$`strata: all cases `
Mean Median
Pre 92.00 92.5
Post 107.05 105.5
The mean and median are approximately the same in preMUA suggesting the data might be Normally distributed. However, postMUA this does not seem likely.
It would be nice to show both plots in one:
both<-ggplot()+geom_boxplot(aes(y=Pre,x=’Pre MUA’),data=plotbox)+geom_boxplot(aes(y=Post,x=’Post MUA’),data=plotbox)+theme_bw()+ggtitle(‘Flexion before and after MUA’)+ylab(label=’max flexion [deg]’)+xlab(label=’Status’)
both
If you are using ggplot < 0.9.2, the title can be set using: opts(title=’Flexion before and after MUA’)
This will show the plot with the x-axis in alphabetical order. The easiest way to change this is by regrouping the data. Create a data-frame called ‘muapre’ for all preoperative data; the first collumn is called ‘flexion’ and the second ‘group’ (which are all “Pre”). Similarly, a ‘muapost’ data-frame is created for all postoperative data with the same column names:
muapre<-data.frame(flexion=plotbox$Pre,group=’Pre’)
muapre
flexion group
1 94 Pre
2 95 Pre
3 89 Pre
4 89 Pre
5 101 Pre
6 76 Pre
7 102 Pre
8 104 Pre
9 103 Pre
10 93 Pre
11 101 Pre
12 92 Pre
13 77 Pre
14 95 Pre
15 89 Pre
16 95 Pre
17 92 Pre
18 84 Pre
19 83 Pre
20 86 Pre
muapost<-data.frame(flexion=plotbox$Post,group=’Post’)
muapost
flexion group
1 115 Post
2 103 Post
3 113 Post
4 122 Post
5 103 Post
6 93 Post
7 118 Post
8 102 Post
9 81 Post
10 102 Post
11 124 Post
12 130 Post
13 103 Post
14 125 Post
15 108 Post
16 106 Post
17 105 Post
18 89 Post
19 113 Post
20 86 Post
Now, bind the rows (rbind) together to create a new data-frame called mua:
mua<-rbind(muapre,muapost)
mua
flexion group
1 94 Pre
2 95 Pre
3 89 Pre
4 89 Pre
5 101 Pre
6 76 Pre
7 102 Pre
8 104 Pre
9 103 Pre
10 93 Pre
11 101 Pre
12 92 Pre
13 77 Pre
14 95 Pre
15 89 Pre
16 95 Pre
17 92 Pre
18 84 Pre
19 83 Pre
20 86 Pre
21 115 Post
22 103 Post
23 113 Post
24 122 Post
25 103 Post
26 93 Post
27 118 Post
28 102 Post
29 81 Post
30 102 Post
31 124 Post
32 130 Post
33 103 Post
34 125 Post
35 108 Post
36 106 Post
37 105 Post
38 89 Post
39 113 Post
40 86 Post
Now the ‘mua’ data-frame can be used to create a grouped box and whisker plot:
muaplot<-ggplot() + stat_boxplot(aes(y = flexion,x = group),data=mua) +theme_bw() + ggtitle(label = ‘Flexion Following MUA’) + ylab(label = ‘Flexion [deg]’)
muaplot
If you are using ggplot < 0.9.2, the title can be set using: opts(title=’Flexion Following MUA’)
