CODEWITHSUNDEEP
rfunctiondataframedplyrtidyverse
rnorouzian
rnorouzian

Reputation: 7517

Making long format selectively pivot_longer() tidyverse in R

I'm trying to make 4 variables (id, uerate, lnw, exper) in my data.frame (d) into long format.

I also want to add two binary (0/1) columns called DL and DE; if the long-formatted value represents lnw the DL==1 and DE==0 and vice versa.

I was wondering how to correctly specify tidyr::pivot_longer() to obtain my EXPECTED OUTPUT below?

d <- read.csv("https://stats.idre.ucla.edu/wp-content/uploads/2016/02/wages_pp-1.txt")

select(d, id, uerate, lnw, exper) %>% pivot_longer(everything()) # tried without success

#### EXPECTED OUTPUT:

##      id uerate variable value DE DL
## 1    31   3.21      lnw 1.491  0  1
## 2    31   3.21      lnw 1.433  0  1
## 3    31   3.21      lnw 1.469  0  1
## 4    31   3.29      lnw 1.749  0  1
## 5    31   2.90      lnw 1.931  0  1
## 6    31   2.50      lnw 1.709  0  1
## 7    31   2.60      lnw 2.086  0  1
## 8    31   4.79      lnw 2.129  0  1
## 6403 31   3.21    exper 0.015  1  0
## 6404 31   3.21    exper 0.715  1  0
## 6405 31   3.21    exper 1.734  1  0
## 6406 31   3.29    exper 2.773  1  0
## 6407 31   2.90    exper 3.927  1  0
## 6408 31   2.50    exper 4.946  1  0
## 6409 31   2.60    exper 5.965  1  0
## 6410 31   4.79    exper 6.984  1  0

Upvotes: 1

Views: 53

Answers (1)

akrun
akrun

Reputation: 887991

We select the columns of interest, and instead of everything() in the columns to select with cols, it should select columns other than 'id', 'uerate' (-c(id, uerate)), then mutate to create new columns 'DE' and 'DL'

library(dplyr)
library(tidyr)
d %>%
   select(id, uerate, lnw, exper) %>% 
   pivot_longer(cols = -c(id, uerate), names_to = 'variable') %>% 
   mutate(DE = +(variable == 'exper'), DL =  +(!DE)) %>%
   arrange(id, variable)

-output

# A tibble: 12,804 x 6
#      id uerate variable value    DE    DL
#   <int>  <dbl> <chr>    <dbl> <int> <int>
# 1    31   3.22 exper    0.015     1     0
# 2    31   3.22 exper    0.715     1     0
# 3    31   3.22 exper    1.73      1     0
# 4    31   3.30 exper    2.77      1     0
# 5    31   2.90 exper    3.93      1     0
# 6    31   2.50 exper    4.95      1     0
# 7    31   2.60 exper    5.96      1     0
# 8    31   4.80 exper    6.98      1     0
# 9    31   3.22 lnw      1.49      0     1
#10    31   3.22 lnw      1.43      0     1
# … with 12,794 more rows

Upvotes: 1

Related Questions