jrepl: Join and Replace Values.

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

Join and Replace Values.

Description

Replace a columns values with matches in a different dataset. Author: Bryce Chamberlain.

Usage

jrepl(
  x,
  y,
  by,
  replace.cols,
  na.only = FALSE,
  only.rows = NULL,
  verbose = FALSE,
  viewalldups = FALSE,
  warn = FALSE
)

Arguments

x	Main dataset which will have new values. This data set will be returned with new values.
y	Supporting dataset which has the id and new values.
by	Vector of join column names. A character vector if the names match. A named character vector if they don't.
replace.cols	Vector of replacement column names, similar format as by.
na.only	Only replace values that are NA.
only.rows	Select rows to be affected. Default checks all rows.
verbose	Print via cat information about the replacement.
viewalldups	Set to TRUE to see all duplicates
warn	Set to TRUE to see warnings.

Value

x with new values.

Examples

df1 = utils::head( sleep )
group.reassign = data.frame( 
  id.num = factor( c( 1, 3, 4 ) ), 
group.replace = factor( c( 99, 99, 99 ) ) 
)

jrepl( 
  x = df1, 
  y = group.reassign, 
  by = c( 'ID' = 'id.num' ), 
  replace.cols = c( 'group' = 'group.replace' ) 
)

# doesn't affect since there are no NAs in group.
jrepl( 
  x = df1,
  y = group.reassign, 
  by = c( 'ID' = 'id.num' ), 
  replace.cols = c( 'group' = 'group.replace' ), 
  na.only = TRUE  
) 

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