Supplying multiple groups of variables to a function for dplyr arguments in the body

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清酒与你
清酒与你 2021-01-18 23:57

Here is the data:

library(tidyverse)

data <- tibble::tribble(
  ~var1, ~var2, ~var3,  ~var4,    ~var5,
    \"a\",   \"d\",   \"g\",  \"hello\",    1L,
           


        
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  • 2021-01-19 00:18

    group_by cannot take groupby_vars... strings as input. You need to use rlang::syms() to turn string vector into variables then use !!! to unquote them so that they can be evaluated inside group_by

    library(tidyverse)
    library(rlang)
    
    data <- tibble::tribble(
      ~var1, ~var2, ~var3,  ~var4,    ~var5,
      "a",   "d",   "g",  "hello",    1L,
      "a",   "d",   "h",  "hello",    2L,
      "b",   "e",   "h",  "k",        4L,
      "b",   "e",   "h",  "k",        7L,
      "c",   "f",   "i",  "hello",    3L,
      "c",   "f",   "i",  "hello",    4L
    )
    
    filter_var <- c("hello")
    groupby_vars1 <- c("var1", "var2", "var3")
    groupby_vars2 <- c("var1", "var2")
    joinby_vars1  <- c("var1", "var2")
    joinby_vars2  <- c("var1", "var2", "var3")
    
    my_fun <- function(data, filter_var, 
                       groupby_vars1, groupby_vars2, 
                       joinby_vars1,  joinby_vars2) {
    
      groupby_vars1 <- syms(groupby_vars1)
      groupby_vars2 <- syms(groupby_vars2)
    
      data2 <- data %>% 
        filter(var4 == filter_var) 
    
      data3 <- data2 %>%
        group_by(!!! groupby_vars1) %>% 
        summarise(var6 = sum(var5))
    
      data4 <- data3 %>%
        ungroup() %>%
        group_by(!!! groupby_vars2) %>% 
        summarise(avg = mean(var6, na.rm = TRUE))
    
      data5 <- data3 %>% 
        left_join(data4, by = joinby_vars1)
    
      data6 <- data %>% 
        left_join(data5, by = joinby_vars2)
    
      return(data6)
    }
    
    my_fun(data, filter_var, 
           groupby_vars1, groupby_vars2, 
           joinby_vars1,  joinby_vars2)
    
    #> # A tibble: 6 x 7
    #>   var1  var2  var3  var4   var5  var6   avg
    #>   <chr> <chr> <chr> <chr> <int> <int> <dbl>
    #> 1 a     d     g     hello     1     1   1.5
    #> 2 a     d     h     hello     2     2   1.5
    #> 3 b     e     h     k         4    NA  NA  
    #> 4 b     e     h     k         7    NA  NA  
    #> 5 c     f     i     hello     3     7   7  
    #> 6 c     f     i     hello     4     7   7
    

    Another way to do it: parse the string vector using parse_exprs outside then unquote them inside the function. See also this

    my_fun2 <- function(data, filter_var, 
                       groupby_vars1, groupby_vars2, 
                       joinby_vars1,  joinby_vars2) {
    
      data2 <- data %>% 
        filter(var4 == filter_var) 
    
      data3 <- data2 %>%
        group_by(!!! groupby_vars1) %>% 
        summarise(var6 = sum(var5))
    
      data4 <- data3 %>%
        ungroup() %>%
        group_by(!!! groupby_vars2) %>% 
        summarise(avg = mean(var6, na.rm = TRUE))
    
      data5 <- data3 %>% 
        left_join(data4, by = joinby_vars1)
    
      data6 <- data %>% 
        left_join(data5, by = joinby_vars2)
    
      return(data6)
    }
    
    my_fun2(data, filter_var, 
            parse_exprs(groupby_vars1), parse_exprs(groupby_vars2), 
            joinby_vars1,  joinby_vars2) 
    
    identical(my_fun(data, filter_var, 
                     groupby_vars1, groupby_vars2, 
                     joinby_vars1,  joinby_vars2),
              my_fun2(data, filter_var, 
                      parse_exprs(groupby_vars1), parse_exprs(groupby_vars2), 
                      joinby_vars1,  joinby_vars2))
    
    [1] TRUE                      
    

    Created on 2018-04-24 by the reprex package (v0.2.0).

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