Dplyr Left Join Multiple Columns

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If you want to use dplyr left join or any other type of join in R to combine information from two or multiple data frames, this post might be very helpful. Here is how to left join only selected columns in R.

The first data frame.

The second data frame.

I realize that dplyr v3.0 allows you to join on different variables. Leftjoin(x, y, by = c('a' = 'b') will match x.a to y.b However, is it possible to join on a combination of variables or do I.

Dplyr Join Select Columns

  1. Currently dplyr supports four types of mutating joins and two types of filtering joins. Mutating joins combine variables from the two data.frames. Innerjoin return all rows from x where there are matching values in y, and all columns from x and y.If there are multiple matches between x and y, all combination of the matches are returned.
  2. According to?fulljoin. By: a character vector of variables to join. 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 join by different variables on x and y use a named vector.
  3. R data frames can be joined on specific columns using one of the dplyr join functions and the by argument. The dplyr join functions can take the additional by argument, which indicates the columns in the “left” and “right” data frames of a join to match on. For example, consider the orders and products data frames of a business. The orders data frame contains five columns: id.
  4. If there are multiple matches between x and y, all combination of the matches are returned. Leftjoin return all rows from x, and all columns from x and y. Dplyr left join select columns. Left join with Dplyr bringing just 1 field form the other table, Use use select to keep only the columns for joining and whatever columns you want to.

How to perform dplyr left join and keep only necessary columns from the second data frame? In this case, let’s keep only elephants and cats.

To do that, use the select function that defines what comes from the second data frame.

Here are two different ways of how to do that.

Dplyr Left Join Multiple Columns Excel

Here is another post that might be useful in your toolbox – multiple left joins in R.

Dplyr join examplesDplyr Left Join Multiple Columns
Source: R/join.r

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

  • inner_join(): includes all rows in x and y.

  • left_join(): includes all rows in x.

  • right_join(): includes all rows in y.

  • full_join(): includes all rows in x or y.

Left

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

Arguments

Dplyr Left Join Multiple Columns Chart

x, y

A pair of data frames, data frame extensions (e.g. a tibble), orlazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, formore details.

by

A character vector of variables to join by.

If NULL, the default, *_join() will perform a natural join, using allvariables in common across x and y. A message lists the variables so that youcan 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$b toy$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 andx$c to y$d.

To perform a cross-join, generating all combinations of x and y,use by = character().

copy

If x and y are not from the same data source,and copy is TRUE, then y will be copied into thesame src as x. This allows you to join tables across srcs, butit is a potentially expensive operation so you must opt into it.

suffix

If there are non-joined duplicate variables in x andy, these suffixes will be added to the output to disambiguate them.Should be a character vector of length 2.

...

Other parameters passed onto methods.

keep

Should the join keys from both x and y be preserved in theoutput?

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, likejoins for database sources, similarly to merge(incomparables = FALSE).

Value

An object of the same type as x. The order of the rows and columns of xis preserved as much as possible. The output has the following properties:

  • For inner_join(), a subset of x rows.For left_join(), all x rows.For right_join(), a subset of x rows, followed by unmatched y rows.For full_join(), all x rows, followed by unmatched y rows.

  • For all joins, rows will be duplicated if one or more rows in x matchesmultiple rows in y.

  • Output columns include all x columns and all y columns. If columns inx and y have the same name (and aren't included in by), suffixes areadded to disambiguate.

  • Output columns included in by are coerced to common type acrossx and y.

  • Groups are taken from x.

Methods

These functions are generics, which means that packages can provideimplementations (methods) for other classes. See the documentation ofindividual methods for extra arguments and differences in behaviour.

Dplyr join examples

Methods available in currently loaded packages:

Dplyr Left Join Multiple Columns Different Names

  • inner_join(): dbplyr (tbl_lazy), dplyr (data.frame).

  • left_join(): dbplyr (tbl_lazy), dplyr (data.frame).

  • right_join(): dbplyr (tbl_lazy), dplyr (data.frame).

  • full_join(): dbplyr (tbl_lazy), dplyr (data.frame).

See also

R Dplyr Left Join Multiple Columns

Examples