reshape data into multiple columns using pivot_longer - r

Question

I am using pivot_longer to reshape my data from wide to long format into multiple value columns. I know there are related questions (Pivot_longer 6 columns to 3 columns or Tidy dataset with pivot_longer: Multiple columns into two columns), but I could not find a solution so far, probably because my two columns will be of different class, the first one being POSIXct and the second one is numeric.
Here is a minimal working example:
structure(list(compid = c("AT9130162999", "AT9090003478", "AT9070005375",
"AT9130048156"), iso2c = c("AT", "AT", "AT", "AT"), nace4 = c("7010",
"4211", "2452", "7010"), lastyear = c("2018", "2019", "2019",
"2019"), `Closing date
Last avail. yr` = structure(c(1546214400,
1577750400, 1585612800, 1577750400), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 1` = structure(c(1514678400,
1546214400, 1553990400, 1546214400), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 2` = structure(c(NA,
1514678400, 1522454400, 1514678400), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 3` = structure(c(NA,
1483142400, 1490918400, 1483142400), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 4` = structure(c(NA,
1451520000, 1459382400, 1451520000), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 5` = structure(c(NA,
1419984000, 1427760000, 1419984000), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 6` = structure(c(NA,
1388448000, 1396224000, 1388448000), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 7` = structure(c(NA,
1356912000, 1364688000, 1356912000), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 8` = structure(c(NA,
1325289600, 1333152000, 1325289600), tzone = "UTC", class = c("POSIXct",
"POSIXt")), `Closing date
Year - 9` = structure(c(NA,
1293753600, 1301529600, 1293753600), tzone = "UTC", class = c("POSIXct",
"POSIXt")), operatinginc_last = c(NA, 482813, -94300, NA), operatinginc_year1 = c(NA,
423482, 780400, NA), operatinginc_year2 = c(NA, 404694, 1210300,
NA), ebit_last = c(1060000, 482813, -94300, 351292), ebit_year1 = c(1501000,
423482, 780400, 331415), ebit_year2 = c(NA, 404694, 1210300,
305492), operatingrev_last = c(28463000, 15842418, 13009700,
11742884), operatingrev_year1 = c(NA, 13734462, 13146300, 10682889
), operatingrev_year2 = c(NA, 13734462, 13146300, 10682889)), row.names = c(NA,
-4L), class = c("tbl_df", "tbl", "data.frame"))
So far, I have tried this:
df_l <- df %>%
pivot_longer(., cols = -(starts_with(c("compid","iso2c","nace4","lastyear","Closing"))),
values_to = "value", values_drop_na=T, names_sep = "_", names_to = c("variable","year"))
But now I would also like to reshape all the columns that start with Closing. How do I do (preferably in one step with pivot_longer)?
The expected output should then include a variable, year and value column, but also a closingdate and date column:
compid iso2c nace4 lastyear `closingdate ~ `date ~`variable ~`year ~ `value
<chr> <chr> <chr> <chr> <dttm> <dttm> <dttm> <dttm>
1 AT913~ AT 7010 2018 `Closing date Last avail. yr` 2018-12-31 ebit last 28463000
2 AT913~ AT 7010 2018 `Closing date Year - 1` 2017-12-31 ebit year1 15362687
2 AT913~ AT 7010 2018 `Closing date Year - 1` 2016-12-31 ebit year2 404694

Answer 1

I have no clue how you would do that in one call to pivot_longer, because you have different variables with different schemes. And you ALSO want to pivot to longer the closing date variable. So here it is in two calls with some cleaning of the closing variable.
library(tidyverse)
df_l <- pivot_longer(df, cols = starts_with("Closing"),
values_to = "date", values_drop_na=T, names_to = c("closing")) %>%
pivot_longer(., cols = contains("_"),
values_to = "value", values_drop_na=T, names_sep = '_', names_to = c("variable",'year')) %>%
mutate(closing = str_remove_all(closing,'Closing date') %>%
str_remove_all(.,'[:cntrl:]') %>%
str_squish() %>%
str_trim())