check_joins: Check the counts before and after join

In emilelatour/lamisc: Latour's Little Helpers

Check the counts before and after join

Description

Before and after using joins, it's important to check the counts of the data sets. This funtions give you the counts for the data you intend to join and the resulting counts for all forms of joins (e.g. left, right, inner, semi, anti, full).

Inner join

An inner_join() only keeps observations from x that have a matching key in y.

The most important property of an inner join is that unmatched rows in either input are not included in the result. This means that generally inner joins are not appropriate in most analyses, because it is too easy to lose observations.

Outer joins

The three outer joins keep observations that appear in at least one of the data frames:

• A left_join() keeps all observations in x.

• A right_join() keeps all observations in y.

• A full_join() keeps all observations in x and y.

Filtering joins

• semi_join() return all rows from x with a match in y.

• anti_join() return all rows from x without a match in y.

Usage

check_joins(x, y, by = NULL)

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). See Methods, below, for more details.

by

A join specification created with join_by(), or 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 on different variables between x and y, use a join_by() specification. For example, join_by(a == b) will match x$a to y$b. To join by multiple variables, use a join_by() specification with multiple expressions. For example, join_by(a == b, c == d) will match x$a to y$b and x$c to y$d. If the column names are the same between x and y, you can shorten this by listing only the variable names, like join_by(a, c). join_by() can also be used to perform inequality, rolling, and overlap joins. See the documentation at ?join_by for details on these types of joins. For simple equality joins, you can alternatively specify a character vector of variable names to join by. For example, by = c("a", "b") joins x$a to y$a and x$b to y$b. If variable names differ between x and y, use a named character vector like by = c("x_a" = "y_a", "x_b" = "y_b").

Value

A tibble.

Examples

library(dplyr)

check_joins(x = band_members,
            y = band_instruments,
            by = "name")

check_joins(x = band_members,
            y = band_instruments,
            by = join_by(name))


band_members <- band_members |>
  mutate(name.x = name,
         name.a = name)

band_instruments <- band_instruments |>
  mutate(name.y = name,
         name.b = name)

check_joins(x = band_members,
            y = band_instruments,
            by = c("name.x" = "name.y"))

check_joins(x = band_members,
            y = band_instruments,
            by = c("name.x" = "name.y",
                   "name.a" = "name.b"))

emilelatour/lamisc documentation built on March 29, 2025, 1:23 p.m.