fjoinf: Full Join with Factors

In oliver-wyman-actuarial/easyr: Helpful Functions from Oliver Wyman Actuarial Consulting

Full Join with Factors

Description

Matches factor levels before full join via merge. Author: Bryce Chamberlain.

Usage

fjoinf(
  data.left,
  data.right,
  by,
  sort.levels = TRUE,
  restrict.levels = FALSE,
  na_level = "(Missing)"
)

Arguments

data.left	Left data. Only rows that matche the join will be included (may still result in duplication).
data.right	Right data. All of this data will be preservered in the join (may also result in duplication).
by	Columns to join on.
sort.levels	Sort the factor levels after combining them.
restrict.levels	Often the joined data won't use all the levels in both datasets. Set to TRUE to remove factor levels that aren't in the joined data.
na_level	some functions don't like factors to have NAs so we replace NAs with this value for factors only. Set NULL to skip.

Value

Joined data, with any factors modified to contain all levels in the joined data.

Examples

df1 = data.frame(
  factor1 = c( 'a', 'b', 'c' ),
  factor2 = c( 'high', 'medium', 'low' ),
  factor.join = c( '0349038u093843', '304359867893753', '3409783509735' ),
  numeric = c( 1, 2, 3 ),
  logical = c( TRUE, TRUE, TRUE )
)

df2 = data.frame(
  factor1 = c( 'd', 'e', 'f' ),
  factor2 = c( 'low', 'medium', 'high' ),
  factor.join = c( '32532532536', '304359867893753', '32534745876' ),
  numeric = c( 4, 5, 6 ),
  logical = c( FALSE, FALSE, FALSE )
)

fjoinf( df1, df2, by = 'factor.join' )

oliver-wyman-actuarial/easyr documentation built on Jan. 27, 2024, 4:37 a.m.