在 R 数据框中插入值的简单查找

Question

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        44485   NA
2        44488   NA
3        43210   NA

There are over 3.5 million records.

Then, I have a second data frame, 'zipcodes'.

market    zip
1         44485
1         44486
1         44488
...       ... (100 zips in market 1)
2         43210
2         43211
...       ... (100 zips in market 2, etc.)

I want to find the correct value for alldata$market for each case based on alldata$zip matching the appropriate value in the zipcode data frame. I'm just looking for the right syntax, and assistance is much appreciated, as usual.

Answer 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") .

Answer 2

另一个对我有用并且非常简单的选择：

alldata$market<-with(zipcodes, market[match(alldata$zip, zip)])

Answer 3

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]

Answer 4

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 .

Answer 5

The syntax of match is a bit clumsy. You might find the lookup package easier to use.

alldata <- data.frame(Case=1:3, zip=c(44485,44488,43210), market=c(NA,NA,NA))
zipcodes <- data.frame(market=c(1,1,1,2,2), zip=c(44485,44486,44488,43210,43211))
alldata$market <- lookup(alldata$zip, zipcodes$zip, zipcodes$market)
alldata
##   Case   zip market
## 1    1 44485      1
## 2    2 44488      1
## 3    3 43210      2