Here is a quick and easy way to perform multiple left joins in R with multiple data frames.
Here are 4 data frames that I would like to join by the column date.
The fastest and easiest way to perform multiple left joins in R is by using reduce function from purrr package and, of course, left_join from dplyr.
When there is no match, the list column is a 0-row tibble with the same column names and types as y. Nestjoin is the most fundamental join since you can recreate the other joins from it. An innerjoin is a nestjoin plus an tidyr::unnest , and leftjoin is a nestjoin plus an unnest (.drop = FALSE). 15.3 innerjoin(superheroes, publishers) innerjoin(x, y): 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. This is a mutating join. 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 have to add a composite key beforehand?
If you have to combine only a few data sets, then other solutions may be nested left_join functions from the dplyr package. For more than 3 data frames, that is quite a struggle.
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I am trying to join two data frames using dplyr. Neither data frame has a unique key column. The closest equivalent of the key column is the dates variable of monthly data. Each df has multiple entries per month, so the dates column has lots of duplicates.
I was able to find a solution from Stack Overflow, but I am having a really difficult time understanding that solution. Can you help me find a simpler solution that is easier for beginner level users to understand?
Here is a simple reproducible example:
Notice that rows 2 & 3 in df_1 both refer to '2018-06-01' (i.e. a duplicate in the key column, other columns have different data)
If I do a simple left_join, I get this:
I want a joined data frame that is something like this:
Here is the Stack Overflow solution that seems to match exactly what I am looking for:
Is it possible to create a solution that is (a) a bit easier to understand for beginners (b) uses the purr package or some other tidyverse solution?
Thanks in advance for any comments and guidance.