do filtering in tidy eval manner.

tidy_filter.R

library(tidyverse)

set.seed(1122)

vecs <- lapply(X = 1:2, function(x) rep(c(1, 2, 3), times = 10) %>% sample() %>% head(10))
names(vecs) <- paste0("col_", 1:2)
dat <- vecs %>% as.data.frame()
dat

# Which col has repeated value more than 3 appearances?
more_than_3 <- function(df, var){
    var <- rlang::sym(var)
    
    df %>% 
        group_by(!!var) %>% 
        summarise(n = n()) %>% 
        filter(n > 3) %>% 
        pull(!!var) %>% 
        range()
}
cols_name <- c("col_1", "col_2")
some_range <- purrr::map(cols_name, more_than_3, df = dat)
names(some_range) <- cols_name
some_range

# Ordinary method
dat %>% 
    filter(col_1 <= some_range[["col_1"]][2], 
           col_2 <= some_range[["col_2"]][2])

# Tidy eval method
my_filter <- function(df, cols){     
    fp <- map(cols, ~quo((!!(as.name(.))) < some_range[[.]][2]))
    print(fp)
    filter(df, !!!fp)
}

my_filter(dat, list("col_1", "col_2"))