How best to unstack this and make for one long data string

Question

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     

Answer 1

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