CODEWITHSUNDEEP
rconditional-statementsleft-join
svenski
svenski

Reputation: 543

How do you do conditional "left join" in R?

I have found myself doing a "conditional left join" several times in R. To illustrate with an example; if you have two data frames such as:

> df
    a b
  1 1 0
  2 2 0

> other.df
    a b
  1 2 3

The goal is to end up with this data frame:

> final.df
    a b
  1 1 0
  2 2 3

The code I've been written so far:

c <- merge(df, other.df, by=c("a"), all.x = TRUE)
c[is.na(c$b.y),]$b.y <- 0
d<-subset(c, select=c("a","b.y"))
colnames(d)[2]<-b

to finally arrive with the result I wanted.

Doing this in effectively four lines makes the code very opaque. Is there any better, less cumbersome way to do this?

Upvotes: 5

Views: 8817

Answers (2)

G. Grothendieck
G. Grothendieck

Reputation: 270195

Here are two ways. In both cases the first line does a left merge returning the required columns. In the case of merge we then have to set the names. The final line in both lines replaces NAs with 0.

merge

res1 <- merge(df, other.df, by = "a", all.x = TRUE)[-2]
names(res1) <- names(df)
res1[is.na(res1)] <- 0

sqldf

library(sqldf)
res2 <- sqldf("select a, o.b from df left join 'other.df' o using(a)")
res2[is.na(res2)] <- 0

Upvotes: 1

Seth
Seth

Reputation: 4795

In two lines:

c <- merge(df, other.df,all=T)
c=c[which(!duplicated(c$a)),]

So this takes the values from both data sets and omits rows with id duplicates from the second. I am not sure which is left and which is right, so if you want the other: flip the data upside down and do the same thing.

c=c[length(c$a):1,]
c=c[which(!duplicated(c$a)),]

Upvotes: 0

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