I created a simple pivot table in the dplyr
package in R. Here is my working example:
library(dplyr)
mean_mpg <- mean(mtcars$mpg)
# creating a new variable that shows that Miles/(US) gallon is greater than the mean or not
mtcars <-
mtcars %>%
mutate(mpg_cat = ifelse(mpg > mean_mpg, 1,0))
mtcars %>%
group_by(as.factor(cyl)) %>%
summarise(sum=sum(mpg_cat),total=n()) %>%
mutate(percentage=sum*100/total)
Now, I want to write a function to reuse this code:
get_pivot <- function(data, predictor,target) {
result <-
data %>%
group_by(as.factor(predictor)) %>%
summarise(sum=sum(target),total=n()) %>%
mutate(percentage=sum*100/total);
print(result)
}
but I receive the following error:
Error in is.factor(x) : object 'cyl' not found
I also tried
get_pivot(mtcars, "cyl", "mpg_cat" )
but it did not work.
What should I do?
If you have the most recent rlang
library update v0.4.0 (June 2019), you can use double curly brackets {{ }}
(aka "curly curly") to make programming with dplyr easier.
# Note: needs installation of rlang 0.4.0 or later
get_pivot <- function(data, predictor,target) {
result <-
data %>%
group_by(as.factor( {{ predictor }} )) %>%
summarise(sum=sum( {{ target }} ),total=n()) %>%
mutate(percentage=sum*100/total);
print(result)
}
# Edit -- thank you Rui Barradas
> get_pivot(mtcars, cyl, mpg_cat)
# A tibble: 3 x 4
`as.factor(cyl)` sum total percentage
<fct> <dbl> <int> <dbl>
1 4 11 11 100
2 6 3 7 42.9
3 8 0 14 0
The reason this is required is that dplyr
and other tidyverse
packages use "non-standard evaluation" like you encounter with some base R functions, like lm(mpg~factor(am),data=mtcars)
. This practice often makes "interactive" code shorter, simpler, and easier to read, but at the cost of making programming more complicated. In this case, the {{ }}
operator serves to transport the column you specify into the context of the function.
https://www.tidyverse.org/articles/2019/06/rlang-0-4-0/
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