How do I convert factor levels to variables in R?

Question

I am relatively new to R and trying to build a population pyramid. I need to have the population data for Males and Females side-by-side in two variables (popMale, pop female). Currently Sex is a factor with 2 levels. How do I convert these 2-factor levels to 2 new variables(popMale, popFemale). I would appreciate any help. Here is a dput snippet of my data:

structure(list(V1 = c("Location", "Dominican Republic", "Dominican Republic", 
"Dominican Republic", "Dominican Republic"), V2 = c("Sex", "Female", 
"Female", "Male", "Male"), V3 = c("Age", "0-4", "5-9", "0-4", 
"5-9"), V4 = c(1950L, 217L, 164L, 223L, 167L), V5 = c(1955L, 
277L, 199L, 286L, 204L)), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -5L))

Answer 1

As your data contains the column names in the first row, the first step to achieve your desired result would be to name your data according to the first row and drop it afterwards. After doing so convert your data to long or tidy format, ie move the years and population numbers in separate columns using eg tidyr::pivot_longer . Finally, you could use tidyr::pivot_wider to spread the data for males and females in separate columns.

Note: Depending on the next steps in your analysis the last step isn't really needed and may actually complicate plotting a population pyramid.

names(df) <- as.character(df[1,])
df <- df[-1,]

library(tidyr) 

df %>% 
  pivot_longer(matches("^\\d+"), names_to = "Year", values_to = "pop") %>% 
  pivot_wider(names_from = Sex, values_from = pop, names_glue = "pop{Sex}")
#> # A tibble: 4 × 5
#>   Location           Age   Year  popFemale popMale
#>   <chr>              <chr> <chr>     <int>   <int>
#> 1 Dominican Republic 0-4   1950        217     223
#> 2 Dominican Republic 0-4   1955        277     286
#> 3 Dominican Republic 5-9   1950        164     167
#> 4 Dominican Republic 5-9   1955        199     204