Reputation: 351
I have a very large data set with variable names that are super abbreviated and it would help immensely if the label in the attr(*, "label") section was extracted and showed up in the column beside the corresponding variable.
label(mtcars[["mpg"]]) <- "Miles/(US) gallon"
label(mtcars[["hp"]]) <- "Gross horsepower"
label(mtcars[["wt"]]) <- "Weight (1000lbs)"
My current code just gets the mean/sd from the entire data set:
mtcars %>% select(mpg, hp, wt) %>% pivot_longer(everything()) %>% group_by(name) %>% summarise(mean=mean(value, na.rm = TRUE), sd=sd(value, na.rm=TRUE))
But I want a column with the label of the variables so it's easier to tell:
name mean sd label
hp 14.7. 68.6 Gross horsepower
mpg 20.1 6.03 Miles/(US) gallon
wt 3.22 0.978 Weight (1000lbs)
I found a thread that sort of gets to what I want, but if I add mutate(labels=label(mtcars)[name])
at the end of the code, I get a column with NA instead of the labels.
Upvotes: 1
Views: 642
Reputation: 887571
We can use imap
library(purrr)
library(dplyr)
library(Hmisc)
imap_dfr(mtcars[c('hp', 'mpg', 'wt')], ~
tibble(name = .y, mean = mean(.x[[1]]),
sd = sd(.x[[1]], na.rm = TRUE),
label = attr(.x, 'label')))
If we use the OP's method, we can also use summarise_all
and then do the pivot_longer
library(tidyr)
mtcars %>%
dplyr::select(mpg, hp, wt) %>%
summarise_all(list(mean = ~mean(., na.rm = TRUE),
sd = ~sd(., na.rm = TRUE),
label = ~attr(., 'label'))) %>%
mutate(rn = 1) %>%
pivot_longer(cols = -rn, names_to = c('name', '.value'), names_sep="_") %>%
select(-rn)
# name mean sd label
#1 mpg 20.09062 6.0269481 Miles/(US) gallon
#2 hp 146.68750 68.5628685 Gross horsepower
#3 wt 3.21725 0.9784574 Weight (1000lbs)
Upvotes: 2