英文:
expand data from column to multiple rows
问题
这是我试图在R中扩展到多列的数据的一个示例练习
Location <- c(rep("ATL", 3), rep("CLE", 3), rep("BOS", 3))
type <- rep(c("sedan", "truck", "coupe"), 3)
pro1 <- rep(c("0800 SC", "1500 SC", "0900 SC"), 3)
pro2 <- rep(c("0800 SC", "1500 SC", "0900 SC"), 3)
pro3 <- rep(c("1000 SC", "1700 SC", "1100 SC"), 3)
pro4 <- rep(c("1300 SC", "1100 SC", "2300 SC"), 3)
x <- data.frame(Location, type, pro1, pro2, pro3, pro4)
我试图将数据转移到Excel文件的屏幕截图
期望的输出（来自Excel的屏幕截图）:
当前的输出:
英文:
This is a practice an example of the data I am trying to expand over multiple columns in R
Location<-c(rep("ATL",3),rep("CLE",3),rep("BOS",3))
type<-rep(c("sedan","truck","coupe"),3)
pro1<-rep(c("0800 SC","1500 SC","0900 SC"),3)
pro2<- rep(c("0800 SC","1500 SC","0900 SC"),3)
pro3<-rep(c("1000 SC","1700 SC","1100 SC"),3)
pro4<-rep(c("1300 SC","1100 SC","2300 SC"),3)
x<-data.frame(Location,type,pro1,pro2,pro3,pro4)
I am trying to transfer the data into the screenshot of the excel file
Desired output (screenshot from Excel):
Current output:
答案1
得分: 0
你只需要使用 tidyr::pivot_longer()。
library(tidyr)
Location<-c(rep("ATL",3),rep("CLE",3),rep("BOS",3))
type<-rep(c("sedan","truck","coupe"),3)
pro1<-rep(c("0800 SC","1500 SC","0900 SC"),3)
pro2<- rep(c("0800 SC","1500 SC","0900 SC"),3)
pro3<-rep(c("1000 SC","1700 SC","1100 SC"),3)
pro4<-rep(c("1300 SC","1100 SC","2300 SC"),3)
x<-data.frame(Location,type,pro1,pro2,pro3,pro4)
x |> pivot_longer(starts_with("pro"), names_to = "pro", values_to = "time")
#> # A tibble: 36 × 4
#> Location type pro time
#> <chr> <chr> <chr> <chr>
#> 1 ATL sedan pro1 0800 SC
#> 2 ATL sedan pro2 0800 SC
#> 3 ATL sedan pro3 1000 SC
#> 4 ATL sedan pro4 1300 SC
#> 5 ATL truck pro1 1500 SC
#> 6 ATL truck pro2 1500 SC
#> 7 ATL truck pro3 1700 SC
#> 8 ATL truck pro4 1100 SC
#> 9 ATL coupe pro1 0900 SC
#> 10 ATL coupe pro2 0900 SC
#> # ℹ 26 more rows
创建于2023-07-05，使用 reprex v2.0.2
英文:
You just need to use tidyr::pivot_longer().
library(tidyr)
Location<-c(rep("ATL",3),rep("CLE",3),rep("BOS",3))
type<-rep(c("sedan","truck","coupe"),3)
pro1<-rep(c("0800 SC","1500 SC","0900 SC"),3)
pro2<- rep(c("0800 SC","1500 SC","0900 SC"),3)
pro3<-rep(c("1000 SC","1700 SC","1100 SC"),3)
pro4<-rep(c("1300 SC","1100 SC","2300 SC"),3)
x<-data.frame(Location,type,pro1,pro2,pro3,pro4)
x |> pivot_longer(starts_with("pro"), names_to = "pro", values_to = "time")
#> # A tibble: 36 × 4
#> Location type pro time
#> <chr> <chr> <chr> <chr>
#> 1 ATL sedan pro1 0800 SC
#> 2 ATL sedan pro2 0800 SC
#> 3 ATL sedan pro3 1000 SC
#> 4 ATL sedan pro4 1300 SC
#> 5 ATL truck pro1 1500 SC
#> 6 ATL truck pro2 1500 SC
#> 7 ATL truck pro3 1700 SC
#> 8 ATL truck pro4 1100 SC
#> 9 ATL coupe pro1 0900 SC
#> 10 ATL coupe pro2 0900 SC
#> # ℹ 26 more rows
<sup>Created on 2023-07-05 with reprex v2.0.2</sup>
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