Pass function arguments by column position to mutate_at
Here's a map2
solution along the lines of Henrik's comment. You can then wrap this inside a custom function. I provided an rough first attempt but I have done minimal tests, so it probably breaks under all sorts of situations if evaluation is strange. It also doesn't use tidyselect for .at
, but neither does modify_at
...
library(tidyverse)
df <- tibble::tribble(
~name, ~life_expectancy, ~poverty, ~household_income,
"New Haven", 78.0580437642378, 0.264221051111753, 42588.7592521085,
"New York", 12.349685329, 0.324067934, 32156.230974623
)
rounded <- df %>%
select(life_expectancy, poverty, household_income) %>%
map2_dfc(
.y = c(1, 2, 0),
.f = ~ round(.x, digits = .y)
)
df %>%
select(-life_expectancy, -poverty, -household_income) %>%
bind_cols(rounded)
#> # A tibble: 2 x 4
#> name life_expectancy poverty household_income
#> <chr> <dbl> <dbl> <dbl>
#> 1 New Haven 78.1 0.26 42589
#> 2 New York 12.3 0.32 32156
modify2_at <- function(.x, .y, .at, .f) {
modified <- .x[.at] %>%
map2(.y, .f)
.x[.at] <- modified
return(.x)
}
df %>%
modify2_at(
.y = c(1, 2, 0),
.at = c("life_expectancy", "poverty", "household_income"),
.f = ~ round(.x, digits = .y)
)
#> # A tibble: 2 x 4
#> name life_expectancy poverty household_income
#> <chr> <dbl> <dbl> <dbl>
#> 1 New Haven 78.1 0.26 42589
#> 2 New York 12.3 0.32 32156
Created on 2018-11-13 by the reprex package (v0.2.1)
2 solutions
mutate
with !!!
invoke
was a good idea but you need it less now that most tidyverse
functions support the !!!
operator, here's what you can do :
digits <- c(life_expectancy = 1, poverty = 2, household_income = 0)
df %>% mutate(!!!imap(digits, ~round(..3[[.y]], .x),.))
# # A tibble: 1 x 4
# name life_expectancy poverty household_income
# <chr> <dbl> <dbl> <dbl>
# 1 New Haven 78.1 0.26 42589
..3
is the initial data frame, passed to the function as a third argument, through the dot at the end of the call.
Written more explicitly :
df %>% mutate(!!!imap(
digits,
function(digit, name, data) round(data[[name]], digit),
data = .))
If you need to start from your old interface (though the one I propose will be more flexible), first do:
digits <- setNames(c(1, 2, 0), c("life_expectancy", "poverty", "household_income"))
mutate_at
and <<-
Here we bend a bit the good practice of avoiding <<-
whenever possible, but readability matters and this one is really easy to read.
digits <- c(1, 2, 0)
i <- 0
df %>%
mutate_at(vars(life_expectancy, poverty, household_income), ~round(., digits[i<<- i+1]))
# A tibble: 1 x 4
# name life_expectancy poverty household_income
# <chr> <dbl> <dbl> <dbl>
# 1 New Haven 78.1 0.26 42589
(or just df %>% mutate_at(names(digits), ~round(., digits[i<<- i+1]))
if you use a named vector as in my first solution)