Replace missing values (NA) in one data set with values from another where columns match

Question

I have a data frame (datadf) with 3 columns, 'x', 'y, and z. Several 'x' values are missing (NA). 'y' and 'z' are non measured variables.

x    y z
153  a 1
163  b 1
NA   d 1
123  a 2 
145  e 2
NA   c 2 
NA   b 1
199  a 2

I have another data frame (imputeddf) with the same three columns:

 x  y z
123 a 1
145 a 2
124 b 1
168 b 2
123 c 1
176 c 2
184 d 1
101 d 2

I wish to replace NA in 'x' in 'datadf' with values from 'imputeddf' where 'y' and 'z' matches between the two data sets (each combo of 'y' and 'z' has its own value of 'x' to fill in).

The desired result:

x    y z
153  a 1
163  b 1
184  d 1
123  a 2 
145  e 2
176  c 2 
124  b 1
199  a 2

I am trying things like:

finaldf <- datadf
finaldf$x <- if(datadf[!is.na(datadf$x)]){ddply(datadf, x=imputeddf$x[datadf$y == imputeddf$y & datadf$z == imputeddf$z])}else{datadf$x}

but it's not working.

What is the best way for me to fill in the NA in the using my imputed value df?

Answer 1

I would do this:

library(data.table)
setDT(DF1); setDT(DF2)

DF1[DF2, x := ifelse(is.na(x), i.x, x), on=c("y","z")]

which gives

     x y z
1: 153 a 1
2: 163 b 1
3: 184 d 1
4: 123 a 2
5: 145 e 2
6: 176 c 2
7: 124 b 1
8: 199 a 2

Comments. This approach isn't so great, since it merges the whole of DF1, while we only need to merge the subset where is.na(x). Here, the improvement looks like (thanks, @Arun):

DF1[is.na(x), x := DF2[.SD, x, on=c("y", "z")]]

This way is analogous to @RHertel's answer.

Answer 2

Here's an alternative with base R:

df1[is.na(df1$x),"x"] <- merge(df2,df1[is.na(df1$x),][,c("y","z")])$x
> df1
#    x y z
#1 153 a 1
#2 163 b 1
#3 124 b 1
#4 123 a 2
#5 145 e 2
#6 176 c 2
#7 184 d 1
#8 199 a 2