Porting Python BoxPlot code to “R”

My previous two entries explained how I am attempting to port the Python code used to create the graph in the DZone article to “R”.

The author of that article published the data that he used to generate the graph. The data consists of several files. I have taken one file and tried to create boxplots from it. I will improve this by combining all the files, parsing them and generating a combined boxplot. But first I coded this “R” script to parse one file and generate a boxplot.

The data from one of the files looks like this.


timeStamp,elapsed,label,responseCode,responseMessage,threadName,dataType,success,Latency
1346999466187,32,Home page - anon,200,OK,Anonymous Browsing 1-2,text,true,31
1346999466182,37,Login form,200,OK,Node save 3-1,text,true,36
1346999466184,35,Home page - anon,200,OK,Anonymous Browsing 1-11,text,true,32
1346999466182,37,Home page - anon,200,OK,Anonymous Browsing 1-1,text,true,34
1346999466189,30,Home page - anon,200,OK,Anonymous Browsing 1-4,text,true,27
1346999466185,46,Home page - anon,200,OK,Anonymous Browsing 1-5,text,true,34
1346999466185,44,Search,200,OK,Search 4-1,text,true,35
1346999466188,28,Home page - anon,200,OK,Anonymous Browsing 1-3,text,true,26
1346999466182,33,Home page - anon,200,OK,Anonymous Browsing 1-7,text,true,32
1346999466182,36,Login Form,200,OK,Perform Login/View Account 5-1,text,true,35
1346999466182,35,Home page - anon,200,OK,Anonymous Browsing 1-10,text,true,33
1346999466182,34,Login Form,200,OK,Authenticated Browsing 2-1,text,true,32
1346999466184,33,Home page - anon,200,OK,Anonymous Browsing 1-6,text,true,31
1346999466182,37,Home page - anon,200,OK,Anonymous Browsing 1-9,text,true,35

It is very easy to parse this and create a “R” data frame.


# TODO: Box Plots
# 
# Author: radhakrishnan
###############################################################################


library(plyr)

options("scipen"=100, "digits"=4)

data <- read.table("~/Documents/Learn R Statistics/R/jmeter_results/4-overall-summary.csv",sep=",",header=T)

head(data)

#I don't think I need 'ddply' here but it serves the purpose.
#It groups the data based on the 'label' and returns the two relevant columns
data <- ddply( data , .variables = "label" , .fun = function(x) x[,c("label","elapsed")])

uniquelables <- as.character(unique(data$label))
lists <- replicate( length(uniquelables),list())

j = 1


for (i in uniquelables ){
  lists[j] = as.list(as.data.frame(data[data$label %in% i,'elapsed']))
  j = j + 1
}

boxplot(lists)

BoxPlot from one file

boxplot

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