Using pivot_longer to turn multiple columns into one in R [duplicate]

Answer 1

Try this:

library(tidyverse)

#Data
df <- structure(list(Region = c("National", "Bejing", "Tianjin", "Hebei"
), X1975 = c(942420, 844.4, 702.86, 4913), X1976 = c(93717, 845.1, 
706.5, 4943), X1977 = c(94974, 860.5, 712.87, 4998), X2008 = c(132802, 
1695, 968.87, 6989)), class = "data.frame", row.names = c(NA, 
-4L))

#Code
df2 <- pivot_longer(df,cols = -Region) %>%
  mutate(name=gsub('X','',name)) %>% rename(Year=name)

# A tibble: 16 x 3
   Region   Year    value
   <chr>    <chr>   <dbl>
 1 National 1975  942420 
 2 National 1976   93717 
 3 National 1977   94974 
 4 National 2008  132802 
 5 Bejing   1975     844.
 6 Bejing   1976     845.
 7 Bejing   1977     860.
 8 Bejing   2008    1695 
 9 Tianjin  1975     703.
10 Tianjin  1976     706.
11 Tianjin  1977     713.
12 Tianjin  2008     969.
13 Hebei    1975    4913 
14 Hebei    1976    4943 
15 Hebei    1977    4998 
16 Hebei    2008    6989 

Answer 2

Here a solution that makes use of num_range for tidy selection of the columns before the call to pivot_longer:

library(dplyr)
library(tidyr)

df_long <- df %>% 
  select(Region, num_range("X", 1975:1999)) %>% 
  pivot_longer(-Region,
               names_to = "Year",
               names_prefix = "X",
               values_to = "Population")

> df_long
# A tibble: 850 x 3
   Region         Year  Population
   <fct>          <chr>      <dbl>
 1 National Total 1975       92420
 2 National Total 1976       93717
 3 National Total 1977       94974
 4 National Total 1978       96259
 5 National Total 1979       97542
 6 National Total 1980       98705
 7 National Total 1981      100072
 8 National Total 1982      101654
 9 National Total 1983      103008
10 National Total 1984      104357
# ... with 840 more rows