SampleData

This is an R Markdown document.

A brief analysis has been performed on the data procured and documented as an R Markdown document.

library(xlsx)

## Loading required package: rJava

## Loading required package: xlsxjars

data11 <- read.xlsx("SampleData.xlsx", sheetName = "SampleData1", header = TRUE)
data22 <- read.xlsx("SampleData.xlsx", sheetName = "SampleData2", header = TRUE)


data2 = data22[complete.cases(data22),]
data1 = data11[complete.cases(data11),]
data1$User = NA

data2$User <- as.character(data2$User)



for(i in data1[,1])
{
  for(q in data2[,1])
  {
      if(data1$Id[i] == data2$Id[q])
      {
  data1$User[i] = data2$User[q]
      }
  }
}

data.1 = data1[complete.cases(data1),]
summary(data1)

##       NA.              Id            Type         Date                    
##  Min.   : 1.00   Min.   :10121   Call  : 7   Min.   :2016-08-04 10:16:47  
##  1st Qu.:15.75   1st Qu.:10137   Email :18   1st Qu.:2016-08-04 15:18:37  
##  Median :30.50   Median :10152   NA    : 1   Median :2016-08-04 16:23:55  
##  Mean   :31.00   Mean   :10158   Update:37   Mean   :2016-08-04 15:33:30  
##  3rd Qu.:46.25   3rd Qu.:10168   Visit : 1   3rd Qu.:2016-08-04 17:05:38  
##  Max.   :62.00   Max.   :10219               Max.   :2016-08-04 19:04:15  
##                                                                           
##      CountA           CountB              CountC              FeedBack 
##  Min.   :0.0367   Min.   :0.0005537   Min.   :0.001932   Others   :27  
##  1st Qu.:0.2371   1st Qu.:0.2111432   1st Qu.:0.344485   NC       :15  
##  Median :0.4064   Median :0.4650753   Median :0.427289   nc       :13  
##  Mean   :0.4813   Mean   :0.4897665   Mean   :0.477077   NA       : 2  
##  3rd Qu.:0.7218   3rd Qu.:0.8149653   3rd Qu.:0.709689   Undecided: 2  
##  Max.   :0.9802   Max.   :0.9840489   Max.   :0.966656   UNDECIDED: 2  
##                                                          (Other)  : 3  
##      User          
##  Length:64         
##  Class :character  
##  Mode  :character  
##                    
##                    
##                    
## 

 newd <- table(data1$Type, data1$User)
 net = as.data.frame.matrix(newd)
 net$Total = net$A1001 + net$A1002 + net$A1003 + net$A1004 + net$A1005
 
 print(net)

##        A1001 A1002 A1003 A1004 A1005 Total
## Call       3     0     1     3     0     7
## Email      2     9     2     1     3    17
## NA         0     1     0     0     0     1
## Update    11     2    19     4     0    36
## Visit      1     0     0     0     0     1

 makeProfilePlot <- function(mylist,names)
{
  require(RColorBrewer)
  # find out how many variables we want to include
  numvariables <- length(mylist)
  # choose 'numvariables' random colours
  colours <- brewer.pal(numvariables,"Set1")
  # find out the minimum and maximum values of the variables:
  mymin <- 1e+20
  mymax <- 1e-20
  for (i in 1:numvariables)
  {
    vectori <- mylist[[i]]
    mini <- min(vectori)
    maxi <- max(vectori)
    if (mini < mymin) { mymin <- mini }
    if (maxi > mymax) { mymax <- maxi }
  }
  # plot the variables
  for (i in 1:numvariables)
  {
    vectori <- mylist[[i]]
    namei <- names[i]
    colouri <- colours[i]
    if (i == 1) { plot(vectori,col=colouri,type="l",ylim=c(mymin,mymax)) }
    else         { points(vectori, col=colouri,type="l")                                     }
    lastxval <- length(vectori)
    lastyval <- vectori[length(vectori)]
    text((lastxval-10),(lastyval),namei,col="black",cex=0.6)
  }
}
 
 
 library(RColorBrewer)
names <- c("A1001", "A1002", "A1003", "A1004", "A1005")
mylist <- list(net$A1001, net$A1002, net$A1003, net$A1004, net$A1005)
makeProfilePlot(mylist,names)
legend("topright", c("A1001", "A1002", "A1003", "A1004", "A1005"), cex = 1.0, fill = rainbow(length(net$A1001)))

 print(net)

##        A1001 A1002 A1003 A1004 A1005 Total
## Call       3     0     1     3     0     7
## Email      2     9     2     1     3    17
## NA         0     1     0     0     0     1
## Update    11     2    19     4     0    36
## Visit      1     0     0     0     0     1

Thank You