CODEWITHSUNDEEP
rdplyrtidyversense
Rasmus Larsen
Rasmus Larsen

Reputation: 6117

Input dplyr::filter() as argument to function

Input dplyr::filter to function

How to create a function which takes any dplyr::filter as input, and returns the number of rows satisfying the filter?

I have tried something like this, which does not work:

library(tidyverse)

filter_function <- function(dataset, filter_text) {
    dataset %>% filter_text %>% nrow() -> n_rows_satisfy_filter

    paste0( "Number of rows satisfying the filter: ", n_rows_satisfy_filter)
}

Here i try to input a filter as a string:

filter_function(iris, "filter( Sepal.Length > 5 & Species == 'setosa' )" )

Gives error:

Error in quote(., filter_text) : 
  2 arguments passed to 'quote' which requires 1

The question is similar but not a duplicate of Using dplyr filter() in programming, because the current question attempts to vary the whole filter, not just the input to a static filter.

Upvotes: 3

Views: 1327

Answers (2)

akrun
akrun

Reputation: 886998

With tidyverse, another option is parse_expr from rlang

library(dplyr)
filter_function <- function(dataset, filter_text) {
  eval(rlang::parse_expr(filter_text)) %>% 
         nrow() %>%
         paste0( "Number of rows satisfying the filter: ", .)
}

filter_function(iris, "filter(dataset, Sepal.Length > 5 & Species == 'setosa' )" )
#[1] "Number of rows satisfying the filter: 22"

Upvotes: 1

myincas
myincas

Reputation: 1530

Try this code, eval evaluates the expr argument in the environment specified by envir and returns the computed value.

library(tidyverse)

filter_function <- function(dataset, filter_text) {
  n_rows_satisfy_filter <- eval(parse(text = filter_text), envir = dataset) %>% nrow()
  paste0( "Number of rows satisfying the filter: ", n_rows_satisfy_filter)
}

filter_function(iris, "filter(dataset, Sepal.Length > 5 & Species == 'setosa' )" )

Upvotes: 3

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