In a dataframe, I have two columns (the names are numbers, due the table being the result of a pivot wider). I'd like to be able to use mutate using these columns but it can't make it work. Here is the data.
df <- structure(list(Age_Band = c("20-30", "20-30", "30-40", "30-40",
"40-50", "40-50", "50-60", "50-60"), Gender = c("female", "male",
"female", "male", "female", "male", "female", "male"), `2012` = c(20881.9,
19962.1, 29710.85, 26187.4, 50536.05, 21359.3, 26447.65, 24520.95
), `2013` = c(20132.4, 17268.15, 22622.1, 21543.05, 39569.15,
15701.1, 21450.95, 21020.6)), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -8L))
This is the code I'm trying to run. To create a new column with the difference.
df %>%
mutate(difference = 2013 - 2012)
It doesn't work, I'm assuming because the column names are numbers? Is there another way to do it? Otherwise is there a way to rename them in dplyr, as I can't find a way to do that either. Any help greatly appreciated. Thanks.
I'd recommend renaming them, e.g using rename_with (or, if you can, avoid creating them in the first place)
library(dplyr)
df %>%
rename_with(~ if_else(grepl("^\\d+$", .x), paste0("var", .x), .x))
# A tibble: 8 × 4
Age_Band Gender var2012 var2013
<chr> <chr> <dbl> <dbl>
1 20-30 female 20882. 20132.
2 20-30 male 19962. 17268.
3 30-40 female 29711. 22622.
4 30-40 male 26187. 21543.
5 40-50 female 50536. 39569.
6 40-50 male 21359. 15701.
7 50-60 female 26448. 21451.
8 50-60 male 24521. 21021.
Just sub works too
df %>%
rename_with(~ sub("^(\\d+)$", "var\\1", .x))
If you have to use the numbers access them by treating them as a symbol by using
eval(as.name("2012"))!!sym("2012")