Programming with dplyr using string as input

user_1391563 0
Viewed 2382

I would like to write a function that uses dplyr inside and I supply variable names as strings. Unfortunately dplyr-s use of NSE makes it rather complicated. From Programming with dplyr I get the following example 

my_summarise <- function(df, var) {
  var <- enquo(var)

  df %>%
    group_by(!!var) %>%
    summarise(a = mean(a))
}

my_summarise(df, g1)

However, I would like to write function where instead of g1 I could provide "g1" and I am not able to wrap my head around how to do that.

dplyr r
3 Answers

Using the .data pronoun from rlang is another option that works directly with column names stored as strings.

The function with .data would look like 

my_summarise <- function(df, var) {
     df %>%
          group_by(.data[[var]]) %>%
          summarise(mpg = mean(mpg))
}

my_summarise(mtcars, "cyl")
# A tibble: 3 x 2
    cyl   mpg
  <dbl> <dbl>
1     4  26.7
2     6  19.7
3     8  15.1
user_24615520

This is how to do it using only dplyr and the very useful as.name function from base R:

my_summarise <- function(df, var) {
  varName <- as.name(var)
  enquo_varName <- enquo(varName)

  df %>%
    group_by(!!enquo_varName) %>%
    summarise(a = mean(a))
}

my_summarise(df, "g1")

Basically, with as.name() we generate a name object that matches var (here var is a string). Then, following Programming with dplyr, we use enquo() to look at that name and return the associated value as a quosure. This quosure can then be unquoted inside the group_by() call using !!.

user_82189040
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