coalesce_join: Coalescing join

In uclalawcovid19behindbars/behindbarstools: Tools for the UCLA Behind Bars Data Team

Coalescing join

Description

Wrapper around dplyr::join and dplyr::coalesce to enable coalescing joins where missing values in 'x' are filled in with matching values from 'y'. Syntax borrowed directly from here: https://alistaire.rbind.io/blog/coalescing-joins/.

Usage

coalesce_join(
  x,
  y,
  by = NULL,
  suffix = c(".x", ".y"),
  join = dplyr::full_join,
  debug = FALSE,
  ...
)

Arguments

x, y	A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr).
by	A character vector of variables to join by. If 'NULL', the default, '*_join()' will perform a natural join, using all variables in common across 'x' and 'y'. A message lists the variables so that you can check they're correct; suppress the message by supplying 'by' explicitly. To join by different variables on 'x' and 'y', use a named vector. For example, 'by = c("a" = "b")' will match 'x$a' to 'y$b'. To join by multiple variables, use a vector with length > 1. For example, 'by = c("a", "b")' will match 'x$a' to 'y$a' and 'x$b' to 'y$b'. Use a named vector to match different variables in 'x' and 'y'. For example, 'by = c("a" = "b", "c" = "d")' will match 'x$a' to 'y$b' and 'x$c' to 'y$d'. To perform a cross-join, generating all combinations of 'x' and 'y', use 'by = character()'.
suffix	If there are non-joined duplicate variables in 'x' and 'y', these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
join	Type of join to perform (e.g. dplyr::left_join).
debug	logical, use coalesce_with_warnings and print debug statements
...	Other parameters passed onto methods.

Value

An object of the same type as 'x'.

Examples

df1 <- data.frame(
    key  = c('a', 'b', 'c', 'd', 'e', 'f'),
    var1 = c(  1,   2,   3,   4,  NA,  NA),
    var2 = c( NA,  NA,  NA,  NA,   5,   6),
    var3 = c(  1,   2,   3,   4,   5,   6)
)

df2 <- data.frame(
    key  = c('c', 'd', 'e', 'f'),
    var1 = c( NA,  NA,   5,   6),
    var2 = c( NA,   4,   5,  NA),
    var4 = c(  3,   4,   5,   6)
)

coalesce_join(df1, df2, by = 'key')

uclalawcovid19behindbars/behindbarstools documentation built on April 22, 2022, 4:08 a.m.