library(readxl)
data <- read_excel("C:/Users/sts-m-06/Desktop/data.xlsx")
head(data)
## # A tibble: 6 x 2
## date country
## <dbl> <chr>
## 1 20180701 Beijing Hongye Hong Food Trade Co.,ltd
## 2 20180701 Ulanqab izawa Chang Trading Co.,ltd
## 3 20180701 Beijing Hongye Hong Food Trade Co.,ltd
## 4 20180701 Beijing Hongye Hong Food Trade Co.,ltd
## 5 20180701 Catalpa Erlianhot city Yang Import Export Trade Co.,ltd
## 6 20180701 Hunan Shangdefu Trading Co.,ltd
c=as.Date(as.character(data$date), "%Y%m%d")
date<-c
date<-transform(date)
new_data<-cbind(date,data)
head(new_data)
## X_data date
## 1 2018-07-01 20180701
## 2 2018-07-01 20180701
## 3 2018-07-01 20180701
## 4 2018-07-01 20180701
## 5 2018-07-01 20180701
## 6 2018-07-01 20180701
## country
## 1 Beijing Hongye Hong Food Trade Co.,ltd
## 2 Ulanqab izawa Chang Trading Co.,ltd
## 3 Beijing Hongye Hong Food Trade Co.,ltd
## 4 Beijing Hongye Hong Food Trade Co.,ltd
## 5 Catalpa Erlianhot city Yang Import Export Trade Co.,ltd
## 6 Hunan Shangdefu Trading Co.,ltd
write.csv(new_data,file = "new_data.csv")
Date year month merge
library(readxl)
library(zoo)
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
data <- read.csv("C:/Users/sts-m-06/Desktop/data.csv")
head(data)
## JIL SAR
## 1 2017 3
## 2 2017 3
## 3 2017 3
## 4 2017 3
## 5 2017 3
## 6 2017 3
Date <- as.Date(paste(data$JIL, data$SAR, sep="-"), "%Y-%M")
d<-as.yearmon(paste(data$JIL, data$SAR), "%Y%m")
newdata<-cbind(d,data)
head(newdata)
## d JIL SAR
## 1 Mar 2017 2017 3
## 2 Mar 2017 2017 3
## 3 Mar 2017 2017 3
## 4 Mar 2017 2017 3
## 5 Mar 2017 2017 3
## 6 Mar 2017 2017 3