Pass a data frame column name to a function

Question

I m trying to write a function to accept a data frame  x  and a column from it  The function performs some calculations on x and later returns another data frame  I m stuck on the best-practices method to pass the column name to the function   The two minimal examples fun1 and fun2 below produce the desired result  being able to perform operations on x column  using max   as an example  However  both rely on the seemingly  at least to me  inelegant    call to substitute   and possibly eval    the need to pass the column name as a character vector       fun1  lt - function x  column     do call  max   list substitute x a   list a   column        fun2  lt - function x  column     max eval  substitute x a   list a   column         df  lt - data frame B   rnorm 10   fun1 df   B   fun2 df   B     I would like to be able to call the function as fun df  B   for example  Other options I have considered but have not tried    Pass column as an integer of the column number  I think this would avoid substitute    Ideally  the function could accept either  with x  get column    but  even if it works  I think this would still require substitute  Make use of formula   and match call    neither of which I have much experience with    Subquestion  Is do call   preferred over eval

User · Answer

If you are trying to build this function within an R package or simply want to reduce complexity, you can do the following:

test_func <- function(df, column) {
  if (column %in% colnames(df)) {
    return(max(df[, column, with=FALSE])) 
  } else {
    stop(cat(column, "not in data.frame columns."))
  }
}

The argument with=FALSE "disables the ability to refer to columns as if they are variables, thereby restoring the “data.frame mode” (per CRAN documentation). The if statement is a quick way to catch if the column name provided is within the data.frame. Could also use tryCatch error handling here.

User · Answer

You can just use the column name directly   df  lt - data frame A 1 10  B 2 11  C 3 12  fun1  lt - function x  column     max x  column     fun1 df   B   fun1 df  c  B   A      There s no need to use substitute  eval  etc   You can even pass the desired function as a parameter   fun1  lt - function x  column  fn      fn x  column     fun1 df   B   max    Alternatively  using    also works for selecting a single column at a time   df  lt - data frame A 1 10  B 2 11  C 3 12  fun1  lt - function x  column     max x  column      fun1 df   B

User · Answer

This answer will cover many of the same elements as existing answers  but this issue  passing column names to functions  comes up often enough that I wanted there to be an answer that covered things a little more comprehensively   Suppose we have a very simple data frame   dat  lt - data frame x   1 4                    y   5 8    and we d like to write a function that creates a new column z that is the sum of columns x and y   A very common stumbling block here is that a natural  but incorrect  attempt often looks like this   foo  lt - function df col name col1 col2         df col name  lt - df col1   df col2       df     Call foo   like this      foo dat z x y    The problem here is that df col1 doesn t evaluate the expression col1  It simply looks for a column in df literally called col1  This behavior is described in  Extract under the section  Recursive  list-like  Objects    The simplest  and most often recommended solution is simply switch from   to    and pass the function arguments as strings   new column1  lt - function df col name col1 col2        Create new column col name as sum of col1 and col2     df  col name    lt - df  col1     df  col2       df     gt  new column1 dat  z   x   y     x y  z 1 1 5  6 2 2 6  8 3 3 7 10 4 4 8 12   This is often considered  best practice  since it is the method that is hardest to screw up  Passing the column names as strings is about as unambiguous as you can get   The following two options are more advanced  Many popular packages make use of these kinds of techniques  but using them well requires more care and skill  as they can introduce subtle complexities and unanticipated points of failure  This section of Hadley s Advanced R book is an excellent reference for some of these issues   If you really want to save the user from typing all those quotes  one option might be to convert bare  unquoted column names to strings using deparse substitute      new column2  lt - function df col name col1 col2       col name  lt - deparse substitute col name       col1  lt - deparse substitute col1       col2  lt - deparse substitute col2        df  col name    lt - df  col1     df  col2       df     gt  new column2 dat z x y    x y  z 1 1 5  6 2 2 6  8 3 3 7 10 4 4 8 12   This is  frankly  a bit silly probably  since we re really doing the same thing as in new column1  just with a bunch of extra work to convert bare names to strings   Finally  if we want to get really fancy  we might decide that rather than passing in the names of two columns to add  we d like to be more flexible and allow for other combinations of two variables  In that case we d likely resort to using eval   on an expression involving the two columns   new column3  lt - function df col name expr       col name  lt - deparse substitute col name       df  col name    lt - eval substitute expr  df parent frame        df     Just for fun  I m still using deparse substitute    for the name of the new column  Here  all of the following will work    gt  new column3 dat z x y    x y  z 1 1 5  6 2 2 6  8 3 3 7 10 4 4 8 12  gt  new column3 dat z x-y    x y  z 1 1 5 -4 2 2 6 -4 3 3 7 -4 4 4 8 -4  gt  new column3 dat z x y    x y  z 1 1 5  5 2 2 6 12 3 3 7 21 4 4 8 32   So the short answer is basically  pass data frame column names as strings and use    to select single columns  Only start delving into eval  substitute  etc  if you really know what you re doing

User · Answer

As an extra thought  if is needed to pass the column name unquoted to the custom function  perhaps match call   could be useful as well in this case  as an alternative to deparse substitute      df  lt - data frame A   1 10  B   2 11   fun  lt - function x  column     arg  lt - match call     max x  arg column       fun df  A    gt   1  10  fun df  B    gt   1  11   If there is a typo in the column name  then would be safer to stop with an error   fun  lt - function x  column  max x  match call   column    fun df  typo    gt  Warning in max x  match call   column     no non-missing arguments to max    gt  returning -Inf   gt   1  -Inf    Stop with error in case of typo fun  lt - function x  column     arg  lt - match call     if  is null x  arg column     stop  Wrong column name     max x  arg column       fun df  typo    gt  Error in fun df  typo   Wrong column name fun df  A    gt   1  10   Created on 2019-01-11 by the reprex package  v0 2 1   I do not think I would use this approach since there is extra typing and complexity than just passing the quoted column name as pointed in the above answers  but well  is an approach

User · Answer

Another way is to use tidy evaluation approach  It is pretty straightforward to pass columns of a data frame either as strings or bare column names  See more about tidyeval here     library rlang  library tidyverse   set seed 123  df  lt - data frame B   rnorm 10   D   rnorm 10     Use column names as strings  fun3  lt - function x             capture strings and create variables   dots  lt - ensyms          unquote to evaluate inside dplyr verbs   summarise at x  vars    dots   list   max    na rm   TRUE       fun3 df   B     gt           B   gt  1 1 715065  fun3 df   B    D     gt           B        D   gt  1 1 715065 1 786913   Use bare column names  fun4  lt - function x             capture expressions and create quosures   dots  lt - enquos          unquote to evaluate inside dplyr verbs   summarise at x  vars    dots   list   max    na rm   TRUE       fun4 df  B    gt           B   gt  1 1 715065  fun4 df  B  D    gt           B        D   gt  1 1 715065 1 786913   gt    Created on 2019-03-01 by the reprex package  v0 2 1 9000

User · Answer

With dplyr it s now also possible to access a specific column of a dataframe  by simply using double curly braces         around the desired column name within the function body  e g  for col name  library tidyverse   fun  lt - function df  col name      df   gt         filter   col name       quot test string quot

User · Answer

Personally I think that passing the column as a string is pretty ugly  I like to do something like   get max  lt - function column data NULL       column lt -eval substitute column  data  parent frame        max column      which will yield    gt  get max mpg mtcars   1  33 9  gt  get max c 1 2 3 4 5    1  5   Notice how the specification of a data frame is optional  you can even work with functions of your columns    gt  get max 1 mpg mtcars   1  0 09615385

[r] Pass a data.frame column name to a function

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