This is a seemingly simple R question, but I don\'t see an exact answer here. I have a data frame (alldata) that looks like this:
Case zip market
1
With such a large data set you may want the speed of an environment lookup. You can use the lookup function from the qdapTools package as follows:
library(qdapTools)
alldata$market <- lookup(alldata$zip, zipcodes[, 2:1])
Or
alldata$zip %l% zipcodes[, 2:1]
Since you don't care about the market column in alldata, you can first strip it off using and merge the columns in alldata and zipcodes based on the zip column using merge:
merge(alldata[, c("Case", "zip")], zipcodes, by="zip")
The by parameter specifies the key criteria, so if you have a compound key, you could do something like by=c("zip", "otherfield").
Another option that worked for me and is very simple:
alldata$market<-with(zipcodes, market[match(alldata$zip, zip)])
Here's the dplyr way of doing it:
library(tidyverse)
alldata %>%
select(-market) %>%
left_join(zipcodes, by="zip")
which, on my machine, is roughly the same performance as lookup.