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rfunctiondplyrdcast

dcast and summary into a function - argument lost


I am trying to turn the following code, which works properly, into a function.

result_check <- data %>% 
  group_by(column, target)  %>%
  summarise(Unique_Elements = n()) %>%
  dcast(column_code ~ target, value.var="Unique_Elements")

For example, if we take the following dataset:

column1 target
  AA      YES
  BB      NO
  BC      NO
  AA      YES

The code would do the aggregate the dataset as per the target variable, like this:

column1    YES   NO
   AA       2    0
   BB       0    1
   BC       0    1  

This is how I construct the function:

aggregate_per_group <- function(column) {
data %>% 
  group_by(column, target)  %>%
  summarise(Unique_Elements = n()) %>%
  dcast(column ~ target, value.var="Unique_Elements")}

But I get - Error: unknown variable to group by : column. I know its a basic question, but any clues why I am loosing the argument in the group_by?

I have tried using the following imlementation "group_by_", as well as "require("dplyr")", but they seem unrelated.


Solution

  • We can use table from base R

    table(data)
    

    If we are interested in a function, then use the group_by_ along with spread from tidyr

    aggregate_per_group <- function(column) {
         data %>% 
            group_by_(column, "target")  %>%
            summarise(Unique_Elements = n()) %>%
            spread(target, Unique_Elements, fill = 0)
     }
    
    library(dplyr)
    library(tidyr)
    aggregate_per_group("column1")
    #  column1    NO   YES
    # *   <chr> <dbl> <dbl>
    #1      AA     0     2
    #2      BB     1     0
    #3      BC     1     0
    

    If we need the dcast from reshape2

    library(reshape2)
    aggregate_per_group <- function(column) {
        data %>% 
           group_by_(column, "target")  %>%
           summarise(Unique_Elements = n()) %>%
           dcast(data = ., paste(column,  '~ target'), 
                  value.var="Unique_Elements", fill = 0)
     }
    
    aggregate_per_group("column1")
    #   column1 NO YES
    #1      AA  0   2
    #2      BB  1   0
    #3      BC  1   0