I have two data frames that I want to join using dplyr. One is a data frame containing first names.
test_data <- data.frame(first_name = c("john", "bill", "madison", "abby", "zzz"),
stringsAsFactors = FALSE)
The other data frame contains a cleaned up version of the Kantrowitz names corpus, identifying gender. Here is a minimal example:
kantrowitz <- structure(list(name = c("john", "bill", "madison", "abby", "thomas"), gender = c("M", "either", "M", "either", "M")), .Names = c("name", "gender"), row.names = c(NA, 5L), class = c("tbl_df", "tbl", "data.frame"))
I essentially want to look up the gender of the name from the test_data
table using the kantrowitz
table. Because I'm going to abstract this into a function encode_gender
, I won't know the name of the column in the data set that's going to be used, and so I can't guarantee that it will be name
, as in kantrowitz$name
.
In base R I would perform the merge this way:
merge(test_data, kantrowitz, by.x = "first_names", by.y = "name", all.x = TRUE)
That returns the correct output:
first_name gender
1 abby either
2 bill either
3 john M
4 madison M
5 zzz <NA>
But I want to do this in dplyr because I'm using that package for all my other data manipulation. The dplyr by
option to the various *_join
functions only lets me specify one column name, but I need to specify two. I'm looking for something like this:
library(dplyr)
# either
left_join(test_data, kantrowitz, by.x = "first_name", by.y = "name")
# or
left_join(test_data, kantrowitz, by = c("first_name", "name"))
What is the way to perform this kind of join using dplyr?
(Never mind that the Kantrowitz corpus is a bad way to identify gender. I'm working on a better implementation, but I want to get this working first.)
This feature has been added in dplyr v0.3. You can now pass a named character vector to the by
argument in left_join
(and other joining functions) to specify which columns to join on in each data frame. With the example given in the original question, the code would be:
left_join(test_data, kantrowitz, by = c("first_name" = "name"))