library("data.table")

#Bring in data
setwd("put datapath here")
data <- fread("realistic_data.txt")

##Mess with dates
data <- data.frame(data)
data$Record_Date <- as.POSIXlt(data$Record_Date,format="%m/%d/%Y %H:%M:%S %p")
data$Record_Date <- as.numeric(data$Record_Date-as.POSIXct("2000-01-01"))

#Back to fast data.table
data <- data.table(data)[order(Cust_ID,Record_Date)]

##Create "list" of comparison dates
data <- data[,list(Cust_ID,Record_Date,Compare_Date=list(I(Record_Date))),by=c("Cust_ID")]

##Calculate the length of the compare date list for each record
#data[,Compare.Cnt:=lapply(Compare_Date,length),by=c("Cust_ID","Record_Date")]

##Create comparable Record_Date list to help with later calculations
#data<-data[,list(Compare_Date,Record_Date2=list(rep(Record_Date,Compare.Cnt))),by=c("Cust_ID","Record_Date")]

##Compare two lists and see of the compare date is within 14 days
data$Within14 <- mapply(FUN = function(RD, CD) {
  d <- as.numeric(CD - RD)
  sum(d > 0 & d <= 14)
}, RD = data$Record_Date, CD = data$Compare_Date)

#My final output data
output <- data[,list(Cust_ID,Record_Date,Within14)][order(Cust_ID,Record_Date)]

#Your data manipulated to work with mine
expected <- fread("expected_results.txt")
names(expected)[3] <-"Exp"
expected <- data.frame(expected)
expected$Record_Date <- as.POSIXlt(expected$Record_Date,format="%m/%d/%Y %H:%M:%S %p")
expected$Record_Date <- as.numeric(expected$Record_Date-as.POSIXct("2000-01-01"))

#Sort expected data
expected <- data.table(expected)[order(Cust_ID,Record_Date)]

#Merge your data onto mine
output <- merge(output,expected,by=c("Cust_ID","Record_Date"))

#Filter to "wrong" entries
output[,Not.Equal:=sum((Within14!=Exp)*1),by="Cust_ID"]

##Look at wrong data
wrong.data <- output[Not.Equal>0][order(Cust_ID,Record_Date)]