Multiple boxplots with predefined statistics using

I have a dataset which looks like this

 VegType    87MIN   87MAX   87Q25   87Q50   87Q75   96MIN   96MAX   96Q25   96Q50     96Q75 00MIN   00MAX   00Q25   00Q50   00Q75
 1          0.02    0.32    0.11    0.12    0.13    0.02    0.26    0.08    0.09    0.10    0.02    0.28    0.10    0.11    0.12
 2          0.02    0.45    0.12    0.13    0.13    0.02    0.20    0.09    0.10    0.11    0.02    0.26    0.11    0.12    0.12
 3          0.02    0.29    0.13    0.14    0.14    0.02    0.27    0.11    0.11    0.12    0.02    0.26    0.12    0.13    0.13
 4          0.02    0.41    0.13    0.13    0.14    0.02    0.58    0.10    0.11    0.12    0.02    0.34    0.12    0.13    0.13
 5          0.02    0.42    0.12    0.13    0.14    0.02    0.46    0.10    0.11    0.11    0.02    0.28    0.12    0.12    0.13
 6          0.02    0.32    0.13    0.14    0.14    0.02    0.52    0.12    0.12    0.13    0.02    0.29    0.13    0.14    0.14
 7          0.02    0.55    0.12    0.13    0.14    0.02    0.24    0.10    0.11    0.11    0.02    0.37    0.12    0.12    0.13
 8          0.02    0.55    0.12    0.13    0.14    0.02    0.19    0.10    0.11    0.12    0.02    0.22    0.11    0.12    0.13

In reality I have 26 variables and 5 years (87,96 and 00 in the column names are years). In an ideal world I would like to have a lattice-like graph with 26 plots, one per variable, with each plot containing 5 boxes, i.e. one per year. I understand that it is not possible to do this is lattice because lattice won't accept predefined statistics. Is there a fairly unpainful way to do this in R with predefined stats? I have used bxp for simple boxplots plotting all the variables for one year in a single plot e.g.

Yr01 = read.csv('dat.csv',header=T)
dat01=t(Yr01[,c("01Min","01Q25","01Mean","01Q75","01Max")])
bxp(list(stats=dat01, n=rep(26, ncol(dat01))),ylim=c(0.07,0.2))

but I don't know how to go from there to what I need.

Thanks.

This can be done, at least using ggplot2, but you'll have to reshape your data quite a bit. And you really have to have a data where the quantiles actually make sense!! Your quantile values are all messed up! For example, Var1 has 01Max = 0.26 and 01Q75 = .67!!

First, I'll recreate a valid data:

n  <- c("01Min", "01Max", "01Med", "01Q25", "01Q75", "02Min", 
                            "02Max", "02Med", "02Q25", "02Q75")
v1 <- c(0.03,  0.76,  0.41,  0.13,  0.67,  0.10,  0.43,  0.27,  0.2,   0.33)
v2 <- c(0.03,  0.28,  0.14,  0.08,  0.20,  0.02,  0.77,  0.13,  0.06, 0.44)

df <- data.frame(v1=v1, v2=v2)
df <- as.data.frame(t(df))
names(df) <- n
df <- cbind(var=c("v1","v2"), df)
> df

#    var 01Min 01Max 01Med 01Q25 01Q75 02Min 02Max 02Med 02Q25 02Q75
# v1  v1  0.03  0.76  0.41  0.13  0.67  0.10  0.43  0.27  0.20  0.33
# v2  v2  0.03  0.28  0.14  0.08  0.20  0.02  0.77  0.13  0.06  0.44

Next, we'll reshape the data:

require(reshape2)
df.m <- melt(df, id="var")
# look for a bunch of numbers from the start of the string and capture it
# in the first variable: () captures the pattern. And replace it with the 
# captured pattern with the variable "\\1"
df.m$year <- gsub("^([0-9]+)(.*$)", "\\1", df.m$variable)

# the same but instead refer to the captured pattern in the second 
# paranthesis using "\\2"
df.m$quan <- gsub("^([0-9]+)(.*)$", "\\2", df.m$variable)
df.f <- dcast(df.m, var+year ~ quan, value.var="value")

To get to this format:

> df.f

#   var year  Max  Med  Min  Q25  Q75
# 1  v1   01 0.76 0.41 0.03 0.13 0.67
# 2  v1   02 0.43 0.27 0.10 0.20 0.33
# 3  v2   01 0.28 0.14 0.03 0.08 0.20
# 4  v2   02 0.77 0.13 0.02 0.06 0.44

Now, we can plot by directly providing the quantile values to corresponding parameters using the corresponding column names as follows:

require(ggplot2)
require(scales)
p <- ggplot(df.f, aes(x=var, ymin=`Min`, lower=`Q25`, middle=`Med`, 
                           upper=`Q75`, ymax=`Max`)) 
p <- p + geom_boxplot(aes(fill=year), stat="identity") 
p

# if you want facetting:
p + facet_wrap( ~ var, scales="free")

You can now accomplish your task of plotting all years for each var in a separate plot using a lapply with this code and subsetting as follows:

lapply(levels(df.f$var), function(x) {
    p <- ggplot(df.f[df.f$var == x, ], 
            aes(x=var, ymin=`Min`, lower=`Q25`, 
                middle=`Med`, upper=`Q75`, ymax=`Max`))
    p <- p + geom_boxplot(aes(fill=year), stat="identity")
    p
    ggsave(paste0(x, ".pdf"), last_plot())
})

Edit: Your data is different from the earlier data you provided in some aspects. So, here's the version of the code for your new data:

# change var to VegType everywhere
require(reshape2)
df.m <- melt(df, id="VegType")

df.m$year <- gsub("^X([0-9]+)(.*$)", "\\1", df.m$variable) # pattern has a X
df.m$quan <- gsub("^X([0-9]+)(.*)$", "\\2", df.m$variable) # pattern has a X
df.f <- dcast(df.m, VegType+year ~ quan, value.var="value")
df.f$VegType <- factor(df.f$VegType) # convert integer to factor

require(ggplot2)
require(scales)
p <- ggplot(df.f, aes(x=VegType, ymin=`MIN`, lower=`Q25`, middle=`Q50`, 
                           upper=`Q75`, ymax=`MAX`)) 
p <- p + geom_boxplot(aes(fill=year), stat="identity") 
p

You can facet/write as separate plots using same code as before.