COMMunication
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baseball_performance.csv
17.3-1.txt

#Part 2 - 도전 미션 3-1 -소스코드

setwd("c:\\r_temp")

data <- read.csv("baseball_performance.csv", header=T)
head(data,25)
bp <- barplot(data$연봉대비출루율, main=paste("야구 선수별 연봉 대비 출루율 분석"), 
       col=rainbow(25) ,
       cex.names=0.7, las=2, names.arg=data$선수명, ylim=c(0,50))

title(ylab="연봉대비출루율", col.lab="red")

# the below can be achieved by mean() function
aver <- 0
for(i in 1:length(data$연봉대비출루율))
   {
     aver <- aver+data$연봉대비출루율[i]
   }
aver

aver <- aver/length(data$연봉대비출루율)
aver

abline(h=aver, col="blue")

text(x=aver-11, y=14.5, col="black", cex=0.8, labels=paste(aver,'%',"(평균출루율)"))
text(x=bp*1.01, y=data$연봉대비출루율*1.05, col="black", cex=0.7, 
   labels=paste(data$연봉대비출루율,'%'))

savePlot("baseball_bar.png",type="png")

# 나이팅게일 챠트로 표현하기
data <- read.csv("주요선수별성적-2013년.csv", header=T)
data

row.names(data) <- data$선수명
data2 <- data[,c(7,8,11,12,13,14,17,19)]
stars(data2,flip.labels=FALSE, draw.segment=TRUE, frame.plot=TRUE, full=TRUE, 
     main=" 야구 선수별 주요 성적 분석-2013년 ")

savePlot("baseball_ny.png",type="png")

label <- names(data2)
val <- table(label)
color <- c("black","red","green","blue","cyan","violet","yellow","grey")
pie(val,labels=label,col=color, radius=0.1, cex=0.6) # 범례용 그래프 만들기
savePlot("baseball_regend.png",type="png")

#연봉대비 출루율과 연봉대비 타점율 표현하기

data4 <- data[,c(2,21,22)]
data4
line1 <- data$연봉대비출루율
line2 <- data$연봉대비타점율
  
par(mar=c(5,4,4,4)+0.1) 
 
plot(line1,type="o",axes=F, ylab="",xlab="",ylim=c(0,50),lty=2,col="blue", 
     main="한국프로야구선수별 기록분석-2013년",lwd=2)
  
axis(1,at=1:25,lab=data4$선수명,las=2)
axis(2,las=1)
par(new=T) 
  
plot(line2,type="o",axes=F, ylab="",xlab="",ylim=c(0,50),lty=2,col="red")
axis(4,las=1) 
mtext(side=4,line=2.5,"연봉대비 타점율") 
mtext(side=2,line=2.5,"연봉대비 출루율") 

abline(h=seq(0,50,5),v=seq(1,25,1),col="gray",lty=2)

legend(18,50,names(data[21:22]),cex=0.8,col=c("red","blue"),lty=1,lwd=2,bg="white")

savePlot("baseball_4.png",type="png")