Error All select() inputs must resolve to integer

Question

I am trying to use dplyr computation as below and then call this in a function where I can change the column name and dataset name. The code is as below:-

sample_table <- function(byvar = TRUE, dataset = TRUE) {
  tcount <-
    df2 %>% group_by(.dots = byvar) %>% tally() %>% arrange(byvar) %>% rename(tcount = n) %>%
    left_join(
      select(
        dataset %>% group_by(.dots = byvar) %>% tally() %>% arrange(byvar) %>% rename(scount = n), byvar, scount
      ), by = c("byvar")
    ) %>%
    mutate_each(funs(replace(., is.na(.), 0)),-byvar %>% mutate(
      tperc = round(tcount / rcount, digits = 2), sperc = round(scount / samplesize, digits = 2),
      absdiff = abs(sperc - tperc)
    ) %>%
    select(byvar, tcount, tperc, scount, sperc, absdiff)
  return(tcount)
}

category_Sample1 <- sample_table(byvar = "category", dataset = Sample1)

My function name is sample_table. The Error message is as below:-

 Error: All select() inputs must resolve to integer column positions.
The following do not:
*  byvar

I know this is a repeat question and I have gone through the below links:- Function writing passing column reference to group_by Error when combining dplyr inside a function

I am not sure where I am going wrong. Any help would be really appreciated please. rcount is the number of rows in df2 and samplesize is the number of rows in "dataset" dataframe I have to compute the same thing for another variable with three different "dataset" names.

Answer 1

You use column references as strings (byvar) (Standard Evaluation) and normal reference (tcount, tperc etc.) (Non Standard Evaluation) together. Make sure you use one of both and the appropriate function: select() or select_(). You can fix your issue by using

select(one_of(c(byvar,'tcount')))