Merge dataframes based on regex condition - r

Question

This problem involves R. I have two dataframes, represented by this minimal reproducible example:
a <- data.frame(geocode_selector = c("36005", "36047", "36061", "36081", "36085"), county_name = c("Bronx", "Kings", "New York", "Queens", "Richmond"))
b <- data.frame(geocode = c("360050002001002", "360850323001019"), jobs = c("4", "204"))
An example to help communicate the very specific operation I am trying to perform: the geocode_selector column in dataframe a contains the FIPS county codes of the five boroughs of NY. The geocode column in dataframe b is the 15-digit ID of a specific Census block. The first five digits of a geocode match a more general geocode_selector, indicating which county the Census block is located in. I want to add a column to b specifying which county each census block falls under, based on which geocode_selector each geocode in b matches with.
Generally, I'm trying to merge dataframes based on a regex condition. Ideally, I'd like to perform a full merge carrying all of the columns of a over to b and not just the county_name.
I tried something along the lines of:
b[, "county_name"] <- NA
for (i in 1:nrow(b)) {
for (j in 1:nrow(a)) {.
if (grepl(data.a$geocode_selector[j], b$geocode[i]) == TRUE) {
b$county_name[i] <- a$county_name[j]
}
}
}
but it took an extremely long time for the large datasets I am actually processing and the finished product was not what I wanted.
Any insight on how to merge dataframes conditionally based on a regex condition would be much appreciated.

Answer 1

You could do this...
b$geocode_selector <- substr(b$geocode,1,5)
b2 <- merge(b, a, all.x=TRUE) #by default it will merge on common column names
b2
geocode_selector geocode jobs county_name
1 36005 360050002001002 4 Bronx
2 36085 360850323001019 204 Richmond
If you wish, you can delete the geocode_selector column from b2 with b2[,1] <- NULL

Answer 2

We can use sub to create the 'geocode_selector' and then do the join
library(data.table)
setDT(a)[as.data.table(b)[, geocode_selector := sub('^(.{5}).*', '\\1', geocode)],
on = .(geocode_selector)]
# geocode_selector county_name geocode jobs
#1: 36005 Bronx 360050002001002 4
#2: 36085 Richmond 360850323001019 204

Answer 3

This is a great opportunity to use dplyr. I also tend to like the string handling functions in stringr, such as str_sub.
library(dplyr)
library(stringr)
a <- data_frame(geocode_selector = c("36005", "36047", "36061", "36081", "36085"),
county_name = c("Bronx", "Kings", "New York", "Queens", "Richmond"))
b <- data_frame(geocode = c("360050002001002", "360850323001019"),
jobs = c("4", "204"))
b %>%
mutate(geocode_selector = str_sub(geocode, end = 5)) %>%
inner_join(a, by = "geocode_selector")
#> # A tibble: 2 x 4
#> geocode jobs geocode_selector county_name
#> <chr> <chr> <chr> <chr>
#> 1 360050002001002 4 36005 Bronx
#> 2 360850323001019 204 36085 Richmond