mutate_joins: Mutating Joins

Description Usage Arguments Value Examples

Description

The mutating joins add columns from y to x, matching rows based on the keys:

If a row in x matches multiple rows in y, all the rows in y will be returned once for each matching row in x.

Usage

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inner_join(
  x,
  y,
  by = NULL,
  suffix = c(".x", ".y"),
  ...,
  na_matches = c("na", "never")
)

left_join(
  x,
  y,
  by = NULL,
  suffix = c(".x", ".y"),
  ...,
  keep = FALSE,
  na_matches = c("na", "never")
)

right_join(
  x,
  y,
  by = NULL,
  suffix = c(".x", ".y"),
  ...,
  keep = FALSE,
  na_matches = c("na", "never")
)

full_join(
  x,
  y,
  by = NULL,
  suffix = c(".x", ".y"),
  ...,
  keep = FALSE,
  na_matches = c("na", "never")
)

Arguments

x, y

The data.frames to join.

by

A character vector of variables to join by. If NULL, the default, *_join() will do a natural join, using all variables with common names across the two tables. A message lists the variables so that you can check they're right (to suppress the message, simply explicitly list the variables that you want to join).

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

character(2). If there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them.

...

Additional arguments to pass to merge()

na_matches

Should NA and NaN values match one another?

The default, "na", treats two NA or NaN values as equal, like %in%, match(), merge().

Use "never" to always treat two NA or NaN values as different, like joins for database sources, similarly to merge(incomparables = FALSE).

keep

logical(1). Should the join keys from both x and y be preserved in the output? Only applies to left_join(), right_join(), and full_join().

Value

A data.frame. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

Examples

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# If a row in `x` matches multiple rows in `y`, all the rows in `y` will be
# returned once for each matching row in `x`
df1 <- data.frame(x = 1:3)
df2 <- data.frame(x = c(1, 1, 2), y = c("first", "second", "third"))
df1 %>% left_join(df2)

# By default, NAs match other NAs so that there are two
# rows in the output of this join:
df1 <- data.frame(x = c(1, NA), y = 2)
df2 <- data.frame(x = c(1, NA), z = 3)
left_join(df1, df2)

# You can optionally request that NAs don't match, giving a
# a result that more closely resembles SQL joins
left_join(df1, df2, na_matches = "never")

poorman documentation built on March 28, 2021, 5:05 p.m.