Merge dataframes on matching A, B and *closest* C?

Question

I have two dataframes like so:

set.seed(1)
df <- cbind(expand.grid(x=1:3, y=1:5), time=round(runif(15)*30))
to.merge <- data.frame(x=c(2, 2, 2, 3, 2),
         


        

Answer 1

mnel's answer uses roll = "nearest" in a data.table join but does not limit to +/- 1 as requested by the OP. In addition, MichaelChirico has suggested to use the on parameter.

This approach uses

• roll = "nearest",
• an update by reference, i.e., without copying,
• setDT() to coerce a data.frame to data.table without copying (introduced 2014-02-27 with v.1.9.2 of data.table),
• the on parameter which spares to set a key explicitely (introduced 2015-09-19 with v.1.9.6).

So, the code below

library(data.table)   # version 1.11.4 used
setDT(df)[setDT(to.merge), on  = .(x, y, time), roll = "nearest",
          val := replace(val, abs(x.time - i.time) > 1, NA)]
df

has updated df:

    x y time  val
 1: 1 1    8 
 2: 2 1   11    c
 3: 3 1   17 
 4: 1 2   27 
 5: 2 2    6 
 6: 3 2   27 
 7: 1 3   28 
 8: 2 3   20 
 9: 3 3   19 
10: 1 4    2 
11: 2 4    6 
12: 3 4    5 
13: 1 5   21 
14: 2 5   12 
15: 3 5   23    d

Note that the order of rows has not been changed (in contrast to Chinmay Patil's answer)

In case df must not be changed, a new data.table can be created by

result <- setDT(to.merge)[setDT(df), on  = .(x, y, time), roll = "nearest",
                .(x, y, time, val = replace(val, abs(x.time - i.time) > 1, NA))]
result

which returns the same result as above.