data<- read.csv("~/Desktop/H % GDP.csv", header=FALSE)
data<-data.frame(t(data)) colnames(data) <- c("Developing","Developed") time<-1996:2013 developing<-data[,1] developed<-data[,2] plot(time,developed,type="l",ylim=c(4.8,6.8),col="red",lwd=3, xlab="Years",xaxt = "n", ylab="Health expenditure, total (% of GDP)" , main="Health Expenditure, Total (% of GDP) from 1996 to 2013") lines(time,developing,col="blue",lwd=3) points(time,developing,pch=15,col="blue") points(time,developed,pch=17,col="red") legend("bottomright", legend=c("Developed","Developing"), title="Type", col=c("red","blue"),lwd=c(3,3,3,3)) axis(1, at=time) life <- read.csv("~/Desktop/Life.csv", header=FALSE) life<-data.frame(t(life)) colnames(life) <- c("Developing","Developed") time<-1996:2013 developing<-life[,1] developed<-life[,2] plot(time,developed,type="l",col="red",ylim=c(65,77),lwd=3, xlab="Years",xaxt = "n", ylab="Life expectancy at birth, total (years)" , main="Life Expectancy at Birth, Total (years) from 1996 to 2013") lines(time,developing,col="blue",lwd=3) points(time,developing,pch=15,col="blue") points(time,developed,pch=17,col="red") legend("bottomright", legend=c("Developed","Developing"), title="Type", col=c("red","blue"),lwd=c(3,3,3,3)) axis(1, at=time)
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final<-read.csv(file.choose())
attach(final) library(plm) reg1<-plm(log(Export.in.1000.USD)~ contig +comlang_off +comlang_ethno +colony +comcol +curcol+ col45 +smctry + log(distcap) +trips.a +trips.b +log(Tariff.a.in.1000) +log(Tariff.b.in.1000)+ log(expenditure.a.in.1000) +log(expenditure.b.in.1000)+ log(GDP.Product) + log(GDP.per.capita.Product)+ factor(year) +factor(country.b) +factor(country.a), data=final,index=c("trade","year"),model="within") fixed.E<-summary(reg1) fixed.E reg2<-plm(log(Export.in.1000.USD)~ contig +comlang_off +comlang_ethno +colony +comcol +curcol+ col45 +smctry + log(distcap) +trips.a +trips.b +log(Tariff.a.in.1000) +log(Tariff.b.in.1000)+ log(expenditure.a.in.1000) +log(expenditure.b.in.1000)+ log(GDP.Product) + log(GDP.per.capita.Product)+ factor(year) +factor(country.b) +factor(country.a), data=final,index=c("trade","year"),model="random") random.E<-summary(reg2) random.E phtest(reg1,reg2) reg3<-plm(log(Import.in.1000.USD)~ contig +comlang_off +comlang_ethno +colony +comcol +curcol+ col45 +smctry + log(distcap) +trips.a +trips.b +log(Tariff.a.in.1000) +log(Tariff.b.in.1000)+ log(expenditure.a.in.1000) +log(expenditure.b.in.1000)+ log(GDP.Product) + log(GDP.per.capita.Product)+ factor(year) +factor(country.b) +factor(country.a), data=final,index=c("trade","year"),model="within") fixed.I<-summary(reg3) fixed.I reg4<-plm(log(Import.in.1000.USD)~ contig +comlang_off +comlang_ethno +colony +comcol +curcol+ col45 +smctry + log(distcap) +trips.a +trips.b +log(Tariff.a.in.1000) +log(Tariff.b.in.1000)+ log(expenditure.a.in.1000) +log(expenditure.b.in.1000)+ log(GDP.Product) + log(GDP.per.capita.Product)+ factor(year) +factor(country.b) +factor(country.a), data=final,index=c("trade","year"),model="random") random.I<-summary(reg4) random.I phtest(reg3,reg4) merge<-read.csv(file.choose(),header=T)
require(xlsx) H28<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H28") H29<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H29") H30<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H30") H32<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H32") H35<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H35") H38<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H38") H40<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H40") H70<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H70") H84<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H84") H87<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H87") H90<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H90") H94<-read.xlsx("/Users/air/Desktop/exp and imp by 2 digital code.xlsx", sheetName = "H94") ph<-read.xlsx("/Users/air/Desktop/exp and imp by three groups.xlsx", sheetIndex =1) ch<-read.xlsx("/Users/air/Desktop/exp and imp by three groups.xlsx", sheetIndex =2) me<-read.xlsx("/Users/air/Desktop/exp and imp by three groups.xlsx", sheetIndex =3) merge<-merge(merge,H28,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H29,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H30,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H32,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H35,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H38,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H40,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H70,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H84,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H87,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H90,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,H94,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,ph,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,ch,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) merge<-merge(merge,me,by.x=c("Country","Year"),by.y=c("country","Year"),all.x=TRUE) write.csv(merge,"final.csv") library(stringr)
data<-read.csv("~/Desktop/11.csv", header=FALSE, stringsAsFactors=FALSE) #import dataset View(data) firstlast<- as.data.frame(strsplit(data[,1], "[,]"))# seperate first, last name transpose<-t(firstlast) transpose[,2]<-substring(as.character(transpose[,2]),2,nchar(as.character(transpose[,2]))) View(transpose) #which(str_detect(transpose[,2],",,")==TRUE) discrepancymiddleinfirst <- str_detect(transpose[,2]," ") #discrepancymiddleinlast <- str_detect(transpose[,1]," ") extractmiddle<-data[which(discrepancymiddleinfirst=="TRUE"),] #rows that have middle name in first name View(extractmiddle) #clean up in 11.csv file email<-t(as.data.frame(strsplit(data[,2], "@")))[,1] discrepancylast <- str_detect(email, ignore.case(transpose[,1])) #detect mismatch discrepancyfirst <- str_detect(email, ignore.case(transpose[,2])) discrepancy<- c(which(discrepancyfirst=="FALSE"),which(discrepancylast=="FALSE")) View(data[discrepancy[duplicated(discrepancy)],]) data<-data[,-1] # rearrange View(data) newdata<-cbind(transpose,data) View(newdata) colnames(newdata) <- c("Last Name","First Name", "Email","Company", "Title", "City","State","Country","Phone") View(newdata) setwd("/Users/air/Desktop") write.csv(newdata, "marketla.csv") |