Question

I have a large dataset, over 1.5 million rows, from 600k unique subjects, so a number of subjects have multiple rows. I am trying to find the cases where the one of the subjects has a DOB entered incorrectly.

test <- data.frame(
    ID=c(rep(1,3),rep(2,4),rep(3,2)),
    DOB = c(rep("2000-03-01",3), "2000-05-06", "2002-05-06",
     "2000-05-06", "2000-05-06", "2004-04-06", "2004-04-06")
)

> test
  ID        DOB
1  1 2000-03-01
2  1 2000-03-01
3  1 2000-03-01
4  2 2000-05-06
5  2 2002-05-06
6  2 2000-05-06
7  2 2000-05-06
8  3 2004-04-06
9  3 2004-04-06

What I am after is some code to basically identify that ‘2’ has an error. I can think of some round about ways using a for loop but that would be computationally inefficient.

Thanks

Answer 1

One approach using plyr:

library(plyr)
  zz <- ddply(test, "ID", summarise, dups = length(unique(DOB)))
  zz[zz$dups > 1 ,]

And if base R is your thing, using aggregate()

zzz <- aggregate(DOB ~ ID, data = test, FUN = function(x) length(unique(x)))
zzz[zzz$DOB > 1 ,]