complete_dt: Complete a data frame with missing combinations of data

In tidyfst: Tidy Verbs for Fast Data Manipulation

Complete a data frame with missing combinations of data

Description

Turns implicit missing values into explicit missing values. All the combinations of column values (should be unique) will be constructed. Other columns will be filled with NAs or constant value.

Usage

complete_dt(.data, ..., fill = NA)

Arguments

.data	data.frame
...	Specification of columns to expand.The selection of columns is supported by the flexible select_dt. To find all unique combinations of provided columns, including those not found in the data, supply each variable as a separate argument. But the two modes (select the needed columns and fill outside values) could not be mixed, find more details in examples.
fill	Atomic value to fill into the missing cell, default uses NA.

Details

When the provided columns with addtion data are of different length, all the unique combinations would be returned. This operation should be used only on unique entries, and it will always returned the unique entries.

If you supply fill parameter, these values will also replace existing explicit missing values in the data set.

Value

data.table

See Also

complete

Examples

df <- data.table(
  group = c(1:2, 1),
  item_id = c(1:2, 2),
  item_name = c("a", "b", "b"),
  value1 = 1:3,
  value2 = 4:6
)

df %>% complete_dt(item_id,item_name)
df %>% complete_dt(item_id,item_name,fill = 0)
df %>% complete_dt("item")
df %>% complete_dt(item_id=1:3)
df %>% complete_dt(item_id=1:3,group=1:2)
df %>% complete_dt(item_id=1:3,group=1:3,item_name=c("a","b","c"))

tidyfst documentation built on July 26, 2023, 5:20 p.m.