How to do vlookup and fill down (like in Excel) in R?

Question

I have a dataset about 105000 rows and 30 columns. I have a categorical variable that I would like to assign it to a number. In Excel, I would probably do something with

Answer 1

If I understand your question correctly, here are four methods to do the equivalent of Excel's VLOOKUP and fill down using R:

# load sample data from Q
hous <- read.table(header = TRUE, 
                   stringsAsFactors = FALSE, 
text="HouseType HouseTypeNo
Semi            1
Single          2
Row             3
Single          2
Apartment       4
Apartment       4
Row             3")

# create a toy large table with a 'HouseType' column 
# but no 'HouseTypeNo' column (yet)
largetable <- data.frame(HouseType = as.character(sample(unique(hous$HouseType), 1000, replace = TRUE)), stringsAsFactors = FALSE)

# create a lookup table to get the numbers to fill
# the large table
lookup <- unique(hous)
  HouseType HouseTypeNo
1      Semi           1
2    Single           2
3       Row           3
5 Apartment           4

Here are four methods to fill the HouseTypeNo in the largetable using the values in the lookup table:

First with merge in base:

# 1. using base 
base1 <- (merge(lookup, largetable, by = 'HouseType'))

A second method with named vectors in base:

# 2. using base and a named vector
housenames <- as.numeric(1:length(unique(hous$HouseType)))
names(housenames) <- unique(hous$HouseType)

base2 <- data.frame(HouseType = largetable$HouseType,
                    HouseTypeNo = (housenames[largetable$HouseType]))

Third, using the plyr package:

# 3. using the plyr package
library(plyr)
plyr1 <- join(largetable, lookup, by = "HouseType")

Fourth, using the sqldf package

# 4. using the sqldf package
library(sqldf)
sqldf1 <- sqldf("SELECT largetable.HouseType, lookup.HouseTypeNo
FROM largetable
INNER JOIN lookup
ON largetable.HouseType = lookup.HouseType")

If it's possible that some house types in largetable do not exist in lookup then a left join would be used:

sqldf("select * from largetable left join lookup using (HouseType)")

Corresponding changes to the other solutions would be needed too.

Is that what you wanted to do? Let me know which method you like and I'll add commentary.

Answer 2

You could use mapvalues() from the plyr package.

Initial data:

dat <- data.frame(HouseType = c("Semi", "Single", "Row", "Single", "Apartment", "Apartment", "Row"))

> dat
  HouseType
1      Semi
2    Single
3       Row
4    Single
5 Apartment
6 Apartment
7       Row

Lookup / crosswalk table:

lookup <- data.frame(type_text = c("Semi", "Single", "Row", "Apartment"), type_num = c(1, 2, 3, 4))
> lookup
  type_text type_num
1      Semi        1
2    Single        2
3       Row        3
4 Apartment        4

Create the new variable:

dat$house_type_num <- plyr::mapvalues(dat$HouseType, from = lookup$type_text, to = lookup$type_num)

Or for simple replacements you can skip creating a long lookup table and do this directly in one step:

dat$house_type_num <- plyr::mapvalues(dat$HouseType,
                                      from = c("Semi", "Single", "Row", "Apartment"),
                                      to = c(1, 2, 3, 4))

Result:

> dat
  HouseType house_type_num
1      Semi              1
2    Single              2
3       Row              3
4    Single              2
5 Apartment              4
6 Apartment              4
7       Row              3