Data:
DB1 <- data.frame(orderItemID = 1:10,
orderDate = c(\"2013-01-21\",\"2013-03-31\",\"2013-04-12\",\"2013-06-01\",\"2014-01-01\", \"2014-02-19\",\"2
You can do:
DB1 =cbind(DB1$orderItemID,as.data.frame(lapply(DB1[-1], as.character)))
days = round(mean(DB1$deliveryDate-DB1$orderDate, na.rm=T))
mask = is.na(DB1$deliveryDate)
DB1$deliveryDate[mask] = DB1$orderDate[mask]+days
# DB1$orderItemID orderDate deliveryDate
#1 1 2013-01-21 2013-01-23
#2 2 2013-03-31 2013-04-01
#3 3 2013-04-12 2013-04-14
#4 4 2013-06-01 2013-06-04
#5 5 2014-01-01 2014-01-03
#6 6 2014-02-19 2014-02-21
#7 7 2014-02-27 2014-02-28
#8 8 2014-10-02 2014-10-04
#9 9 2014-10-31 2014-11-01
#10 10 2014-11-21 2014-11-23
I re-arrange your data since they were not clean:
DB1 <- data.frame(orderItemID = 1:10,
orderDate = c("2013-01-21","2013-03-31","2013-04-12","2013-06-01","2014-01-01", "2014-02-19","2014-02-27","2014-10-02","2014-10-31","2014-11-21"),
deliveryDate = c("2013-01-23", "2013-04-01", NA, "2013-06-04", "2014-01-03", NA, "2014-02-28", "2014-10-04", "2014-11-01", "2014-11-23"))