Hemant Sain

2017-Oct-09 10:40 UTC

### [R] Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)

I'm getting all the rows as NA in Cscore and almost most of the observation in R and F and M are also NA. what can be the reason for this. also suggest me the appropriate solution. On 9 October 2017 at 15:51, Jim Lemon <drjimlemon at gmail.com> wrote:> Hi Hemant, > Here is an example that might answer your questions. Please don't run > previous code as it might not work. > > I define the break values as arguments to the function > (rbreaks,fbreaks,mbreaks) If you want the breaks to work, make sure that > they cover the range of the input values, otherwise you get NAs. > > # expects a three (or more) column data frame where > # column 1 is customer ID, column 2 is amount of purchase > # and column 3 is date of purchase > qdrfm<-function(x,rbreaks=3,fbreaks=3,mbreaks=3,date.format="%Y-%m-%d", > weights=c(1,1,1),finish=NA) { > > # if no finish date is specified, use current date > if(is.na(finish)) finish<-as.Date(date(), "%a %b %d %H:%M:%S %Y") > x$rscore<-as.numeric(finish-as.Date(x[,3],date.format)) > x$rscore<-as.numeric(cut(x$rscore,breaks=rbreaks,labels=FALSE)) > custIDs<-unique(x[,1]) > ncust<-length(custIDs) > rfmout<-data.frame(custID=custIDs,rscore=rep(0,ncust), > fscore=rep(0,ncust),mscore=rep(0,ncust)) > rfmout$rscore<-cut(by(x$rscore,x[,1],min),breaks=rbreaks,labels=FALSE) > rfmout$fscore<-cut(table(x[,1]),breaks=fbreaks,labels=FALSE) > rfmout$mscore<-cut(by(x[,2],x[,1],sum),breaks=mbreaks,labels=FALSE) > rfmout$cscore<-(weights[1]*rfmout$rscore+ > weights[2]*rfmout$fscore+ > weights[3]*rfmout$mscore)/sum(weights) > return(rfmout[order(rfmout$cscore),]) > } > > set.seed(12345) > x2<-data.frame(ID=sample(1:50,250,TRUE), > purchase=round(runif(250,5,100),2), > date=paste(rep(2016,250),sample(1:12,250,TRUE), > sample(1:28,250,TRUE),sep="-")) > > # example 1 > qdrfm(x2) > > # example 2 > qdrfm(x2,rbreaks=c(0,200,400),fbreaks=c(0,5,10),mbreaks=c(0,350,700), > finish=as.Date("2017-01-01")) > > Jim > >-- hemantsain.com [[alternative HTML version deleted]]

Jim Lemon

2017-Oct-09 20:57 UTC

### [R] Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)

I seriously doubt that you are running the code I sent. What you have probably done is to run your data, which has a different date format, without changing the breaks or the date format arguments. As you haven't provided any example that shows what you are doing, I can't guess what the problem is. Jim On Mon, Oct 9, 2017 at 9:40 PM, Hemant Sain <hemantsain55 at gmail.com> wrote:> I'm getting all the rows as NA in Cscore and almost most of the observation > in R and F and M are also NA. > what can be the reason for this. also suggest me the appropriate solution. > > On 9 October 2017 at 15:51, Jim Lemon <drjimlemon at gmail.com> wrote: >> >> Hi Hemant, >> Here is an example that might answer your questions. Please don't run >> previous code as it might not work. >> >> I define the break values as arguments to the function >> (rbreaks,fbreaks,mbreaks) If you want the breaks to work, make sure that >> they cover the range of the input values, otherwise you get NAs. >> >> # expects a three (or more) column data frame where >> # column 1 is customer ID, column 2 is amount of purchase >> # and column 3 is date of purchase >> qdrfm<-function(x,rbreaks=3,fbreaks=3,mbreaks=3,date.format="%Y-%m-%d", >> weights=c(1,1,1),finish=NA) { >> >> # if no finish date is specified, use current date >> if(is.na(finish)) finish<-as.Date(date(), "%a %b %d %H:%M:%S %Y") >> x$rscore<-as.numeric(finish-as.Date(x[,3],date.format)) >> x$rscore<-as.numeric(cut(x$rscore,breaks=rbreaks,labels=FALSE)) >> custIDs<-unique(x[,1]) >> ncust<-length(custIDs) >> rfmout<-data.frame(custID=custIDs,rscore=rep(0,ncust), >> fscore=rep(0,ncust),mscore=rep(0,ncust)) >> rfmout$rscore<-cut(by(x$rscore,x[,1],min),breaks=rbreaks,labels=FALSE) >> rfmout$fscore<-cut(table(x[,1]),breaks=fbreaks,labels=FALSE) >> rfmout$mscore<-cut(by(x[,2],x[,1],sum),breaks=mbreaks,labels=FALSE) >> rfmout$cscore<-(weights[1]*rfmout$rscore+ >> weights[2]*rfmout$fscore+ >> weights[3]*rfmout$mscore)/sum(weights) >> return(rfmout[order(rfmout$cscore),]) >> } >> >> set.seed(12345) >> x2<-data.frame(ID=sample(1:50,250,TRUE), >> purchase=round(runif(250,5,100),2), >> date=paste(rep(2016,250),sample(1:12,250,TRUE), >> sample(1:28,250,TRUE),sep="-")) >> >> # example 1 >> qdrfm(x2) >> >> # example 2 >> qdrfm(x2,rbreaks=c(0,200,400),fbreaks=c(0,5,10),mbreaks=c(0,350,700), >> finish=as.Date("2017-01-01")) >> >> Jim >> > > > > -- > hemantsain.com

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