R ggplot2 and boxplot() - different plots?-CodePudding

I have data of measurements at 9 locations, that I want to visualize with grouped boxplot. For each location, there are 3 groups ("combined", "No Rain", "Rain"), where "combined" ist just the data of "No Rain" and "Rain" combined.

I first created grouped boxplots using boxplot():

mydata <- read.table(file = "mydata.txt",  
                        skip=0, head=TRUE, sep="\t", dec = ".",
                        stringsAsFactors=FALSE)

#Rain
boxplot(Value~Location, data=mydata, subset = Variable =="Rain", col = "deepskyblue",
        boxwex = 1, outline = FALSE, at = c(10, 20, 30, 40, 50, 60, 70, 80, 90),
        xlab = "Location", ylab = "Value",
        cex.axis = 2, cex.lab = 2)     

#combined
boxplot(Value~Location, data=mydata, subset = Variable =="combined", col = "grey",
        at = c(8, 18, 28, 38, 48, 58, 68, 78, 88),boxwex = 1, add = TRUE,
        outline = FALSE, names = NA, xaxt = 'n', yaxt = 'n')


#No Rain
boxplot(Value~Location, data=mydata, subset = Variable =="No Rain", col = "indianred1", add = TRUE,
        boxwex = 1, at = c(12, 22, 32, 42, 52, 62, 72, 82, 92),  outline = FALSE,
        names = NA, xaxt = 'n', yaxt = 'n')

When I create grouped boxplots with the same data, but with ggplot2, the plot looks different, the values seem to be distributed differentl.

mydata$Location <- as.character(mydata$Location)

ggplot(mydata, aes(x = Location, y = Value, fill = Variable, na.rm = TRUE))  
  geom_boxplot(outlier.shape = NA, na.rm = TRUE)  
  scale_fill_manual(values=c("grey","red","lightblue"))  
  scale_y_continuous(limits = c(0, 3.7), 
                     breaks = c(0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5))

Is there an explanation for this?

data:

structure(list(Location = c("1", "1", "1", "1", "1", "1", "1", 
"1", "1", "1", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", 
"3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "4", "4", "4", 
"4", "4", "4", "4", "4", "4", "4", "5", "5", "5", "5", "6", "6", 
"6", "6", "7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "8", 
"8", "8", "8", "8", "8", "8", "8", "8", "8", "9", "9", "9", "9", 
"9", "9", "9", "9", "9", "9", "1", "1", "1", "1", "1", "1", "1", 
"1", "1", "1", "1", "1", "1", "2", "2", "2", "2", "2", "2", "2", 
"2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", "3", "3", 
"3", "3", "3", "3", "3", "3", "4", "4", "4", "4", "4", "4", "4", 
"4", "4", "4", "4", "4", "4", "5", "5", "5", "5", "5", "5", "5", 
"5", "5", "5", "5", "5", "5", "6", "6", "6", "6", "6", "6", "6", 
"6", "6", "6", "6", "6", "6", "7", "7", "7", "7", "7", "7", "7", 
"7", "7", "7", "7", "7", "7", "8", "8", "8", "8", "8", "8", "8", 
"8", "8", "8", "8", "8", "8", "9", "9", "9", "9", "9", "9", "9", 
"9", "9", "9", "9", "9", "9", "1", "1", "1", "1", "1", "1", "1", 
"1", "1", "1", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", 
"3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "4", "4", "4", 
"4", "4", "4", "4", "4", "4", "4", "5", "5", "5", "5", "6", "6", 
"6", "6", "7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "8", 
"8", "8", "8", "8", "8", "8", "8", "8", "8", "9", "9", "9", "9", 
"9", "9", "9", "9", "9", "9", "1", "1", "1", "1", "1", "1", "1", 
"1", "1", "1", "1", "1", "1", "2", "2", "2", "2", "2", "2", "2", 
"2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", "3", "3", 
"3", "3", "3", "3", "3", "3", "4", "4", "4", "4", "4", "4", "4", 
"4", "4", "4", "4", "4", "4", "5", "5", "5", "5", "5", "5", "5", 
"5", "5", "5", "5", "5", "5", "6", "6", "6", "6", "6", "6", "6", 
"6", "6", "6", "6", "6", "6", "7", "7", "7", "7", "7", "7", "7", 
"7", "7", "7", "7", "7", "7", "8", "8", "8", "8", "8", "8", "8", 
"8", "8", "8", "8", "8", "8", "9", "9", "9", "9", "9", "9", "9", 
"9", "9", "9", "9", "9", "9"), Value = c(0.04, 0.02, 0.02, 0.01, 
0, 0.02, 0.01, 0, 0.07, 0, 0, 0, 0.05, 0.01, 0.01, 0.03, 0, 0, 
0.04, 0, 0.04, 0.01, 0.03, 0.05, 0.07, 0.16, 0.02, 0.04, 0.33, 
0.58, 0.04, 0.03, 0.02, 0.01, 0.03, 0.08, 0.05, 0.12, 0.33, 0.05, 
0, 0, 0.04, 0.05, 0.01, 0.01, 0, 0.05, 0.02, 0.01, 0.01, 0.02, 
0.01, 0.09, 0.01, 0.02, 0.07, 0.25, 0.02, 0.02, 0.01, 0.03, 0.01, 
0.05, 0, 0.03, 0, 0.08, 0, 0, 0, 0, 0.01, 0, 0, 0, 0.11, 0.05, 
0, 2.6, 0.1, 0, 1, 0, 0.29, NA, NA, 0.29, 0.2, 0, 0, 0, 1.4, 
0.14, 0, 0.3, 0.14, 0.29, NA, NA, 1, 0.52, 0, 0.02, 0.2, 2.6, 
0.1, 0.25, 0.2, 0.23, 5, NA, NA, 2.14, 0.92, 0.01, 0.04, 0.09, 
4.6, 0.34, 1, 1.2, 0.55, 1.71, NA, NA, 1.14, 0.48, 0.02, 0.02, 
0.09, 8.6, 0.46, 0.16, 0.7, 2.36, 3.57, NA, NA, 3.14, 0.4, 0.02, 
0.04, 0.03, 1.4, 0.06, 0.09, 0, 0.23, 0.71, NA, NA, 1.14, 0.28, 
0, 0, 0.1, 5.4, 0.16, 0.25, 1.2, 0.82, 4, NA, NA, 1.86, 0.4, 
0.01, 0.02, 0.17, 1, 0.72, 0.63, 0.5, 0.59, 2.14, NA, NA, 0.71, 
0.4, 0.01, 0.02, 0.06, 3.6, 0.06, 0.63, 1.3, 0.68, 14.57, NA, 
NA, 0.71, 0.12, 0, 0.01, 0.04, 0.02, 0.02, 0.01, 0, 0.02, 0.01, 
0, 0.07, 0, 0, 0, 0.05, 0.01, 0.01, 0.03, 0, 0, 0.04, 0, 0.04, 
0.01, 0.03, 0.05, 0.07, 0.16, 0.02, 0.04, 0.33, 0.58, 0.04, 0.03, 
0.02, 0.01, 0.03, 0.08, 0.05, 0.12, 0.33, 0.05, 0, 0, 0.04, 0.05, 
0.01, 0.01, 0, 0.05, 0.02, 0.01, 0.01, 0.02, 0.01, 0.09, 0.01, 
0.02, 0.07, 0.25, 0.02, 0.02, 0.01, 0.03, 0.01, 0.05, 0, 0.03, 
0, 0.08, 0, 0, 0, 0, 0.01, 0, 0, 0, 0.11, 0.05, 0, 2.6, 0.1, 
0, 1, 0, 0.29, NA, NA, 0.29, 0.2, 0, 0, 0, 1.4, 0.14, 0, 0.3, 
0.14, 0.29, NA, NA, 1, 0.52, 0, 0.02, 0.2, 2.6, 0.1, 0.25, 0.2, 
0.23, 5, NA, NA, 2.14, 0.92, 0.01, 0.04, 0.09, 4.6, 0.34, 1, 
1.2, 0.55, 1.71, NA, NA, 1.14, 0.48, 0.02, 0.02, 0.09, 8.6, 0.46, 
0.16, 0.7, 2.36, 3.57, NA, NA, 3.14, 0.4, 0.02, 0.04, 0.03, 1.4, 
0.06, 0.09, 0, 0.23, 0.71, NA, NA, 1.14, 0.28, 0, 0, 0.1, 5.4, 
0.16, 0.25, 1.2, 0.82, 4, NA, NA, 1.86, 0.4, 0.01, 0.02, 0.17, 
1, 0.72, 0.63, 0.5, 0.59, 2.14, NA, NA, 0.71, 0.4, 0.01, 0.02, 
0.06, 3.6, 0.06, 0.63, 1.3, 0.68, 14.57, NA, NA, 0.71, 0.12, 
0, 0.01), Variable = c("No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "No Rain", "No Rain", "No Rain", "No Rain", 
"No Rain", "No Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", "Rain", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined", "combined", "combined", "combined", 
"combined", "combined", "combined")), row.names = c(NA, -390L
), class = "data.frame")

CodePudding user response：

I think your problem is caused by the use of limits on your call to scale_y_continuous. This appears to be filtering the data before calculating the statistics used for the box and whisker plots.

The solution is to use coord_cartesian(). This allows ggplot to use the whole dataframe to calculate the statistics and then "zooms" the plot to required size and location:

ggplot(d, aes(x = Location, y = Value, fill = Variable, na.rm = TRUE))  
       geom_boxplot(outlier.shape = NA, na.rm = TRUE)  
       scale_fill_manual(values=c("grey","red","lightblue"))  
       scale_y_continuous(breaks = c(0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5))   
       coord_cartesian(ylim=c(0, 3.7))

See this page for more details.