actor <- c("kim", "lee", "hyun")gender <- c("M", "F", "M")boxoffice2012 <- c(100, 110, 120)boxoffice2014 <- c(100, 80, 160)actordf <- data.frame(actor, gender,boxoffice2012, boxoffice2014) actordft <- t(actordf)actordft str(actordft ) require(reshape) # gender 가없었을때 돌아가던 것actordf_m1 <- melt(actordf, id=c("actor"))actordf_m1 # gender 가..

경기도 버스 201207~101212 평일 TransitBusPass_wd12071212.csv TransitBusPass_주말(11.09-11.12).xls TransitBusPass_주말(12.01-12.06).xls TransitBusPass_주말(12.07-12.12).xls TransitBusPass_평일(11.09-11.12).xls TransitBusPass_평일(12.01-12.06).xls ggtr <- read.csv('TransitBusPass_wd12071212.csv') head(ggtr$지역,3) length(ggtr$지역) darea1 <- sqldf('sel..

#----------- daywsie patterns --------- applesam$dateH <- as.numeric(substr (as.character(applesam $datetimeStr),12,13) ) applesam_h$dateH applesam_h <- sqldf("select dateH, avg (apple) as avg_app, avg(samsung) as avg_sams,count(*) as cntfrom applesamgroup by dateH" ) plot(applesam_h$avg_app,ylim=yrange, type="b", col=2)lines(applesam_h$avg_sams,type="b", col=3) applesam_..

applesamsung20150628.csv #============== read.csv("")applesam<-read.csv ("applesamsung20150628.csv")str(applesam) # converting date typeshttp://www.statmethods.net/input/dates.h tml names(applesam)[1] <- "datetimeStr"applesam$dateD <- as.Date(substr (applesam$datetimeStr,1,10))head(applesam,3) ncomp <- nrow(applesam)-1tmp<- applesam$dateD[2:nrow(applesam)]-apple..

cctv_pop3.csv #-------[CCTV location info]---------------------- cctv3 <- cctv1[4:nrow(cctv1),c(1,2,4)] #View(cctv3) names(cctv3) <- c("ku","Y2011","Y2012") cctv3$ku <- as.character(cctv3$ku) cctv3$Y2011<-gsub(",","",as.character(cctv3$Y2011)) cctv3$Y2011 <- as.numeric(cctv3$Y2011) cctv3$Y2012<-gsub(",","",as.character(cctv3$Y2012)) cctv3$Y2012 <- as.numer..

# MERGE 연습 rcrashes3 <- merge(crashes, roads, by="Road", all = TRUE) nrow(rcrashes3) rcrashes4 <- merge(crashes, roads, by="Road") nrow(rcrashes4) roads1 <- roads names(roads1)[1] <- "roadname" rcrashes5 <- merge(crashes, roads1, by.x = "Road", by.y = "roadname")