CODEWITHSUNDEEP
rdata.tablegroupingaggregatesummary
nilsole
nilsole

Reputation: 1723

data.table: Group by, then aggregate with custom function returning several new columns

In data.table, how can I do the following:

The trick here is to generate several new columns without calling the aggregation function more than once.

Example:

library(data.table)
mtcars_dt <- data.table(mtcars)

returnsOneColumn <- function(dt_group_all_columns){
  "returned_value_1"
}

# works great, returns one new column as summary per group
mtcars_dt[,
          list( new_column_1 = returnsOneColumn(dt_group_all_columns= .SD) ),
          by = c("mpg", "cyl"),
          .SDcols = colnames(mtcars_dt)
          ]

returnsMultipleColumns <- function (dt_group_all_columns){
  list( "new_column_1" = "returned_value_1", 
        "new_column_2" = "returned_value_2"  )
}

# does not work: Ideally, I would like to have mpg, cyl, and several columns 
# generated from once calling returnsMultipleColumns
mtcars_dt[,
          list( returnsMultipleColumns(dt_group_all_columns = .SD) ),
          by = c("mpg", "cyl"),
          .SDcols = colnames(mtcars_dt)
          ]

# desired output should look like this
#
#     mpg cyl     new_column_1     new_column_2
# 1: 21.0   6 returned_value_1 returned_value_2
# 2: 22.8   4 returned_value_1 returned_value_2
# 3: 21.4   6 returned_value_1 returned_value_2
# 4: 18.7   8 returned_value_1 returned_value_2

Related:

Assign multiple columns using := in data.table, by group

Upvotes: 0

Views: 900

Answers (1)

Onyambu
Onyambu

Reputation: 79198

You are already returning a list from the function. You do not need to list them again. So remove the list and have the code like below

mtcars_dt[,
           returnsMultipleColumns(dt_group_all_columns = .SD),
           by = c("mpg", "cyl"),
           .SDcols = colnames(mtcars_dt)
           ]
     mpg cyl     new_column_1     new_column_2
 1: 21.0   6 returned_value_1 returned_value_2
 2: 22.8   4 returned_value_1 returned_value_2
 3: 21.4   6 returned_value_1 returned_value_2
 4: 18.7   8 returned_value_1 returned_value_2

Upvotes: 1

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