R Merge By Two Columns

 admin

The data frames must have same column names on which the merging happens. Merge Function in R is similar to database join operation in SQL. The different arguments to merge allow you to perform natural joins i.e. Inner join, left join, right join,cross join, semi join, anti join and full outer join. We can perform Join in R using merge Function or by using family of join functions in dplyr package. # Make a data frame mapping story numbers to titles stories Merge the two data frames merge (stories, data, 'storyid. To Concatenate two columns of dataframe in R we generally use paste Function. Concatenate or join of two string column in R & integer columns in R is accomplished by Paste function. We can also concatenate or join numeric and string column. Let’s see how to.

Source: R/join.r

These are generic functions that dispatch to individual tbl methods - see themethod documentation for details of individual data sources. x andy should usually be from the same data source, but if copy isTRUE, y will automatically be copied to the same source as x.

Arguments

x, y

tbls to join

by

a character vector of variables to join by. If NULL, thedefault, *_join() will do a natural join, using all variables withcommon names across the two tables. A message lists the variables sothat you can check they're right (to suppress the message, simplyexplicitly 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 toy.b.

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, for instance, na_matchesto control how NA values are matched. See join.tbl_df for more.

keep

If TRUE the by columns are kept in the nesting joins.

name

the name of the list column nesting joins create. If NULL the name of y is used.

Join types

Currently dplyr supports four types of mutating joins, two types of filtering joins, anda nesting join.

Mutating joins combine variables from the two data.frames:

R merge by two columns using
inner_join()

return all rows from x where there are matchingvalues in y, and all columns from x and y. If there are multiple matchesbetween x and y, all combination of the matches are returned.

R Merge By Two Columns Excel

left_join()

return all rows from x, and all columns from xand y. Rows in x with no match in y will have NA values in the newcolumns. If there are multiple matches between x and y, all combinationsof the matches are returned.

right_join()

return all rows from y, and all columns from xand y. Rows in y with no match in x will have NA values in the newcolumns. If there are multiple matches between x and y, all combinationsof the matches are returned.

Right Join In R

R Merge By Two Columns
full_join()

return all rows and all columns from both x and y.Where there are not matching values, returns NA for the one missing.

Filtering joins keep cases from the left-hand data.frame:

semi_join()

return all rows from x where there are matchingvalues in y, keeping just columns from x. A semi join differs from an inner join because an inner join will returnone row of x for each matching row of y, where a semijoin will never duplicate rows of x.

anti_join()

return all rows from x where there are notmatching values in y, keeping just columns from x.

Nesting joins create a list column of data.frames:

R Merge By Two ColumnsMerge in r by two columns

R Merge By Two Columns Using

nest_join()

return all rows and all columns from x. Adds alist column of tibbles. Each tibble contains all the rows from ythat match that row of x. When there is no match, the list column isa 0-row tibble with the same column names and types as y. nest_join() is the most fundamental join since you can recreate the other joins from it.An inner_join() is a nest_join() plus an tidyr::unnest(), and left_join() is anest_join() plus an unnest(.drop = FALSE).A semi_join() is a nest_join() plus a filter() where you check that every element of data hasat least one row, and an anti_join() is a nest_join() plus a filter() where you check every element has zero rows.

Grouping

Groups are ignored for the purpose of joining, but the result preservesthe grouping of x.

R Combine Dataframe Columns

Examples