##########################################################################################
# Designed and developed by Tinniam V Ganesh
# Date : 1 Jul 2015
# Function: relativeBowlingER
# This function computes and plots the relative bowling Economy Rate of the bowlers
#
###########################################################################################
relativeBowlingER <- function(frames, names) {
col1 <- rainbow(length(frames))
for(i in 1:length(frames))
{
# Clean the bowler data frame
bowler <- cleanBowlerData(frames[[i]])
# Get the max wickets taken by bowler
wkts <- c(0:max(bowler$Wkts))
#compute mean economy rate for the bowler
eRate <- ER(frames[[i]])
# Plot the Economy Rate vs Wickets
if(i == 1) {
plot(wkts,eRate,type="o",pch=13,col=col1[i],lwd=3,
xlab="wickets",ylab="Economy rate",main="Relative economy rate")
}
lines(wkts,eRate,col=col1[i],lwd=3.0)
}
#i <- 1
type = rep(1,length(frames))
width = rep(2.5,length(frames))
legend(x="topright",legend=names, lty=type,
lwd=width,col=col1,bty="n",cex=0.8)
mtext("Data source-Courtesy:ESPN Cricinfo", side=1, line=4, adj=1.0, cex=0.8, col="blue")
}
ER <- function(file){
# Clean the bowler data before processing
bowler <- cleanBowlerData(file)
econRate <- NULL
# Calculate mean economy rate versus number of wickets taken. Loop for 0 to max wickets
for (i in 0: max(as.numeric(as.character(bowler$Wkts)))) {
# Create a vector of Economy rate for number of wickets 'i'
a <- bowler[bowler$Wkts == i,]$Econ
b <- as.numeric(as.character(a))
# Compute the mean economy rate by using lapply on the list
econRate[i+1] <- lapply(list(b),mean)
}
econRate
}
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