How to use function arguement to set column name

Question

I have dataframe df as follows:

df <- data.frame(x = c(\"A\", \"A\", \"B\", \"B\"), y = 1:4)

And I have a function that fin

Answer 1

We can make use of the quosure from the devel version of dplyr (soon to be released 0.6.0)

generateVarMean <- function(df, x, y) {
   x <- enquo(x)
   y <- enquo(y)
   newName <- paste0(quo_name(y), ".mean")
   df %>%
       select(UQ(x), UQ(y)) %>%
       group_by(UQ(x)) %>%
       summarise(UQ(newName) := mean(UQ(y), na.rm = TRUE))            
 }

generateVarMean(df1, a, b)
# A tibble: 2 × 2
#       a b.mean
#  <fctr>  <dbl>
#1      A    1.5
#2      B    3.5

We get the input arguments as quosure with enquo, convert the quosure to string with quo_name to create 'newName' string. Then, evaluate the quosure inside select/group_by/summarise by unquoting (UQ or !!). Note that in the new version, we can also assign the column names directly and using the assign operator (:=)

Answer 2

No need to add anything to the function. Just replace paste0("y", ".mean") with paste0(deparse(substitute(y)), ".mean")

So now the function and the output will be:

> generateVarMean <- function(df, x, y) {
   mean.df <- df %>%
     select(x, y) %>%
     group_by(x) %>%
     dplyr::summarise(variable.mean = mean(y, na.rm = TRUE))
 colnames(mean.df)[2] <- paste0(deparse(substitute(y)), ".mean")
 print(mean.df)
 }

> generateVarMean(df, a, b)
# A tibble: 2 × 2
       x b.mean
  <fctr>  <dbl>
1      A    1.5
2      B    3.5