Propagate Column — propagate • dunlin

propagatecopy columns from a given table of a list of data.frame to all tables based on other common columns. If several rows are associated with the same key, the rows will be duplicated in the receiving tables. In safe mode, the key must be unique in the original table.

Usage

propagate(db, from, add, by, safe = TRUE)

# S3 method for list
propagate(db, from, add, by, safe = TRUE)

Arguments

db: (list of data.frame) object for which some variable need to be propagated.
from: (string) the name of the table where the variables to propagate are stored.
add: (character) the names of the variables to propagate.
by: (character) the key binding the from table to the other tables.
safe: (flag) should the key be checked for uniqueness in the from table.

Value

updated list of data.frame.

Examples

df1 <- data.frame(
  id1 = c("a", "a", "c", "d", "e", "f"),
  id2 = c("A", "B", "A", "A", "A", "A"),
  int = c(1, 2, 3, 4, 5, 6),
  bool = c(TRUE, FALSE, TRUE, FALSE, TRUE, FALSE)
)

df2 <- data.frame(
  id1 = c("a", "a", "d", "e", "f", "g"),
  id2 = c("A", "B", "A", "A", "A", "A")
)

df3 <- data.frame(
  id1 = c("a", "c", "d", "e", "f", "x"),
  id2 = c("A", "A", "A", "A", "B", "A"),
  int = c(11, 22, 33, 44, 55, 66)
)

db <- list(df1 = df1, fd2 = df2, df3 = df3)
propagate(db, from = "df1", add = c("int", "bool"), by = c("id1", "id2"))
#> 
#> Updating: fd2 with: int, bool
#> Updating: df3 with: bool
#> $df1
#>   id1 id2 int  bool
#> 1   a   A   1  TRUE
#> 2   a   B   2 FALSE
#> 3   c   A   3  TRUE
#> 4   d   A   4 FALSE
#> 5   e   A   5  TRUE
#> 6   f   A   6 FALSE
#> 
#> $fd2
#>   id1 id2 int  bool
#> 1   a   A   1  TRUE
#> 2   a   B   2 FALSE
#> 3   d   A   4 FALSE
#> 4   e   A   5  TRUE
#> 5   f   A   6 FALSE
#> 6   g   A  NA    NA
#> 
#> $df3
#>   id1 id2 int  bool
#> 1   a   A  11  TRUE
#> 2   c   A  22  TRUE
#> 3   d   A  33 FALSE
#> 4   e   A  44  TRUE
#> 5   f   B  55    NA
#> 6   x   A  66    NA
#>