Ordering boxplots can be tricky sometimes. There I present 3 boxplots. The first one is the most classic one. The second one is the same boxplot but ordered. The third one does the work for a multifactorial data frame. The code is given below for the 3 examples separately.


### Exemple 1 : Usual boxplot

# Create data :7 varieties of wheat / 20 samples per variety / a numeric value for each sample
variety=c(rep("soldur", 20) , rep("silur", 20) , rep("lloyd", 20), rep("pescadou", 20),
        rep("X4582", 20) , rep("Dudur", 20) , rep("Classic", 20))
note=c( sample(2:5, 20 , replace=T) , sample(6:10, 20 , replace=T),
        sample(1:7, 30 , replace=T), sample(3:10, 70 , replace=T) )
data=data.frame(variety, note)

# Basic boxplot
boxplot(data$note ~ data$variety , col="grey")

### Exemple 1 : Usual boxplot

# Create data :7 varieties of wheat / 20 samples per variety / a numeric value for each sample

variety=c(rep("soldur", 20) , rep("silur", 20) , rep("lloyd", 20), rep("pescadou", 20),

rep("X4582", 20) , rep("Dudur", 20) , rep("Classic", 20))

note=c( sample(2:5, 20 , replace=T) , sample(6:10, 20 , replace=T),

sample(1:7, 30 , replace=T), sample(3:10, 70 , replace=T) )

data=data.frame(variety, note)

# Basic boxplot

boxplot(data$note ~ data$variety , col="grey")


### Exemple 2 : Ordered boxplot

# Create data :7 varieties of wheat / 20 samples per variety / a numeric value for each sample
variety=c(rep("soldur", 20) , rep("silur", 20) , rep("lloyd", 20), rep("pescadou", 20),
        rep("X4582", 20) , rep("Dudur", 20) , rep("Classic", 20))
note=c( sample(2:5, 20 , replace=T) , sample(6:10, 20 , replace=T),
        sample(1:7, 30 , replace=T), sample(3:10, 70 , replace=T) )
data=data.frame(variety, note)

# Create a vector named "new_order" containing the desired order, and ask to boxplot using this vector !
new_order <- with(data, reorder(variety , note, median , na.rm=T))

# And draw the boxplot
boxplot(data$note ~ new_order , ylab="sickness" , col="darkgreen", boxwex=0.4 , main="")

### Exemple 2 : Ordered boxplot

# Create data :7 varieties of wheat / 20 samples per variety / a numeric value for each sample

variety=c(rep("soldur", 20) , rep("silur", 20) , rep("lloyd", 20), rep("pescadou", 20),

rep("X4582", 20) , rep("Dudur", 20) , rep("Classic", 20))

note=c( sample(2:5, 20 , replace=T) , sample(6:10, 20 , replace=T),

sample(1:7, 30 , replace=T), sample(3:10, 70 , replace=T) )

data=data.frame(variety, note)

# Create a vector named "new_order" containing the desired order, and ask to boxplot using this vector !

new_order <- with(data, reorder(variety , note, median , na.rm=T))

# And draw the boxplot

boxplot(data$note ~ new_order , ylab="sickness" , col="darkgreen", boxwex=0.4 , main="")


### Exemple 3 : Multifactorial ordered boxplot

# Create data
# This time we still have several varieties of wheat. But each genotype have 20 samples grown in high temperature, 
# and 20 in low temperature. So we have 2 factors : variety and treatment.

variety=c(rep("soldur" , 40), rep("silur" , 40), rep("lloyd" , 40), 
          rep("pescadou" , 40) , rep("X4582" , 40) , 
          rep("Dudur" , 40) , rep("Classic" , 40))

treatment= rep(c(rep("high" , 20) , rep("low" , 20)) , 7)

note=c( rep(c(sample(0:4, 20 , replace=T) , sample(1:6, 20 , replace=T)),2), 
          rep(c(sample(5:7, 20 , replace=T), sample(5:9, 20 , replace=T)),2), 
          c(sample(0:4, 20 , replace=T) , sample(2:5, 20 , replace=T), 
          rep(c(sample(6:8, 20 , replace=T) , sample(7:10, 20 , replace=T)),2) ))

data=data.frame(variety, treatment ,  note)


# I reorder the variety from the most sensible to the most resistant. (mixing low and high treatments for the calculations)
new_order <- with(data, reorder(variety , note, mean , na.rm=T))

# Then I make the boxplot, asking to use the 2 factors : variety (in the good order) AND treatment :
par(mar=c(3,4,3,1))
myplot=boxplot(note ~ treatment*new_order , data=data  , boxwex=0.4 , ylab="sickness",
        main="sickness of several wheat lines" , col=c("slateblue1" , "tomato") ,  xaxt="n")

# To add the label of x axis
my_names=sapply(strsplit(myplot$names , '\\.') , function(x) x[[2]] )
my_names=my_names[seq(1 , length(my_names) , 2)]
axis(1, at = seq(1.5 , 14 , 2), labels = my_names , tick=FALSE , cex=0.3)
for(i in seq(0.5 , 20 , 2)){ abline(v=i,lty=1, col="grey")}

# Add a legend
legend("bottomright", legend = c("High treatment", "Low treatment"), col=c("slateblue1" , "tomato"),
       pch = 15, bty = "n", pt.cex = 3, cex = 1.2,  horiz = F, inset = c(0.1, 0.1))

### Exemple 3 : Multifactorial ordered boxplot

# Create data

# This time we still have several varieties of wheat. But each genotype have 20 samples grown in high temperature,

# and 20 in low temperature. So we have 2 factors : variety and treatment.

variety=c(rep("soldur" , 40), rep("silur" , 40), rep("lloyd" , 40),

rep("pescadou" , 40) , rep("X4582" , 40) ,

rep("Dudur" , 40) , rep("Classic" , 40))

treatment= rep(c(rep("high" , 20) , rep("low" , 20)) , 7)

note=c( rep(c(sample(0:4, 20 , replace=T) , sample(1:6, 20 , replace=T)),2),

rep(c(sample(5:7, 20 , replace=T), sample(5:9, 20 , replace=T)),2),

c(sample(0:4, 20 , replace=T) , sample(2:5, 20 , replace=T),

rep(c(sample(6:8, 20 , replace=T) , sample(7:10, 20 , replace=T)),2) ))

data=data.frame(variety, treatment , note)

# I reorder the variety from the most sensible to the most resistant. (mixing low and high treatments for the calculations)

new_order <- with(data, reorder(variety , note, mean , na.rm=T))

# Then I make the boxplot, asking to use the 2 factors : variety (in the good order) AND treatment :

par(mar=c(3,4,3,1))

myplot=boxplot(note ~ treatment*new_order , data=data , boxwex=0.4 , ylab="sickness",

main="sickness of several wheat lines" , col=c("slateblue1" , "tomato") , xaxt="n")

# To add the label of x axis

my_names=sapply(strsplit(myplot$names , '\\.') , function(x) x[[2]] )

my_names=my_names[seq(1 , length(my_names) , 2)]

axis(1, at = seq(1.5 , 14 , 2), labels = my_names , tick=FALSE , cex=0.3)

for(i in seq(0.5 , 20 , 2)){ abline(v=i,lty=1, col="grey")}

# Add a legend

legend("bottomright", legend = c("High treatment", "Low treatment"), col=c("slateblue1" , "tomato"),

pch = 15, bty = "n", pt.cex = 3, cex = 1.2, horiz = F, inset = c(0.1, 0.1))

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5 Comments on "#9 Ordered Boxplot"

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EmmaBTSS

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Hi,
I already have a table with equivalent treatments and varieties, as well as the percentage and its standard error and confidence intervals. I plot the % but I would like to add the confidence intervals on the plot so it would make a box as well as the standard error. COuld you help ? Thanks