dplyr pipeline in a function - r

Question

I'm trying to put a dplyr pipeline in a function but after reading the vignette multiple times as well as the tidy evaluation (https://tidyeval.tidyverse.org/dplyr.html).
I still can't get it to work...
#Sample data:
dat <- read.table(text = "A ID B
1 X 83
2 X NA
3 X NA
4 Y NA
5 X 2
6 Y 2
12 Y 10
7 Y 18
8 Y 85", header = TRUE)
# What I'm trying to do:
x <- dat %>% filter(!is.na(B)) %>% count('ID') %>% filter(freq>3)
x$ID
# Now in a function:
n_occurences <- function(df, n, column){
# Group by ID and return IDs with number of non-na > n in column
column <- enquo(column)
x <- df %>%
filter(!is.na(!!column)) %>%
count('ID') %>% filter(freq>n)
x$ID
}
# Let's try:
col <- 'B'
n_occurences(dat, n=3, column = col)
There is no error, but the output is wrong. This as something to do with the tidy evaluation, but I just can't get my head around it.

Answer 1

With rlang_0.40, we can do this much easier by using the {{...}} or curly-curly operator
library(rlang)
library(dplyr)
n_occurences <- function(df, n1, column){
df %>%
filter(!is.na({{column}})) %>%
count(ID) %>%
filter(n > n1) %>%
pull(ID)
}
n_occurences(dat, n1 = 3, column = B)
#[1] Y
#Levels: X Y
If we intend to pass a quoted string, convert it to symbol (sym) and then do the evaluation (!!)
n_occurences <- function(df, n1, column){
column <- rlang::sym(column)
df %>%
filter(!is.na(!!column)) %>%
count(ID) %>%
filter(n > n1) %>%
pull(ID)
}
col <- 'B'
n_occurences(dat, n1=3, column = col)
#[1] Y
#Levels: X Y