Below is the sample data and the desired result. Yes, I know that there are four columns not listed in the desired out. It is just to keep it simple. Figuring if I can get the first four created then the next four are not that bad. Any ideas on how to accomplish this? My first attempts have been to use pivot_wider but struggling to get the column names that have year and month to create.

 state <- c(32,32,32,32,32,32,32,32)
 indcode <-c(44,44,44,44,45,45,45,45)
 area <-c("000000","000000","000000","000000","000000","000000","000000","000000")
 areatype <-c("01","01","01","01","01","01","01","01")
 ownership <-c("00","00","00","00","00","00","00","00")
 periodyear  <-c(2018,2019,2020,2021,2018,2019,2020,2021)
 January <- c(44,90,45,91,46,92,48,96)
 February <- c(44,91,46,91,48,92,49,99)


 example <- data.frame(state,indcode,area,areatype,ownership,periodyear,January,February)


 state      indcode      area    areatype     ownership     2018m1     2018m2   2019m1    2019 m2    
 32            44       000000      01            00           44         44       90         91          
 32            45       000000      01            00           46         48       92        92     

CodePudding user response：

library(tidyverse)
example %>%
  pivot_longer(January:February, names_to = "month") %>%
  mutate(mo_num = match(month, month.name)) %>%
  mutate(col_name = paste(periodyear, mo_num, sep = "m")) %>%
  select(-periodyear, -month, -mo_num) %>%
  pivot_wider(names_from = col_name, values_from = value)

Result

# A tibble: 2 x 13
  state indcode area   areatype ownership `2018m1` `2018m2` `2019m1` `2019m2` `2020m1` `2020m2` `2021m1` `2021m2`
  <dbl>   <dbl> <chr>  <chr>    <chr>        <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>
1    32      44 000000 01       00              44       44       90       91       45       46       91       91
2    32      45 000000 01       00              46       48       92       92       48       49       96       99