Those particular attributes are created by readr. By design, they (and all attributes of a tibble) are automatically dropped after you modify the data, e.g. with mutate.
Reprex:
library(readr)
cars1 <- read_csv(readr_example("mtcars.csv"),
col_types = cols_only(mpg = "d", cyl = "i"))
str(cars1)
#> Classes 'tbl_df', 'tbl' and 'data.frame': 32 obs. of 2 variables:
#> $ mpg: num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
#> $ cyl: int 6 6 4 6 8 6 8 4 4 6 ...
#> - attr(*, "spec")=
#> .. cols_only(
#> .. mpg = col_double(),
#> .. cyl = col_integer(),
#> .. disp = col_skip(),
#> .. hp = col_skip(),
#> .. drat = col_skip(),
#> .. wt = col_skip(),
#> .. qsec = col_skip(),
#> .. vs = col_skip(),
#> .. am = col_skip(),
#> .. gear = col_skip(),
#> .. carb = col_skip()
#> .. )
cars2 <- tibble::rowid_to_column(cars1)
str(cars2)
#> Classes 'tbl_df', 'tbl' and 'data.frame': 32 obs. of 3 variables:
#> $ rowid: int 1 2 3 4 5 6 7 8 9 10 ...
#> $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
#> $ cyl : int 6 6 4 6 8 6 8 4 4 6 ...
In your case, they're actually giving you useful information, though. All your data has been turned into factors (which is a problem—factors of numbers are a frequent source of bugs), but the attributes list correct types for most of the columns. Something strange is afoot.