similar to: RFM Analysis Help

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:

hello, I'm confused what you guys are talking about. i just want to set ideal threshold values for my RFM scores which can be done using Quantiles but i don't want to use quantiles because my data is not normally distributed so it will lead to wrong ranges of breaks. to fix this problem I'm looking for an approach which can define the ideal range to breaks to categorize RFM scores into

> On Oct 13, 2017, at 2:51 AM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > > Hi > > You expect us to solve your problem but you ignore advice already recieved. > > Your data are unreadable, use dput(yourdata) instead. see ?dput > >> test<-read.table("clipboard", heade=T) > Error in scan(file = file, what = what, sep = sep, quote = quote,

Hello Jim, i have converted all my variable data type according to your attached example including date, and my dataset looks like this. ID purchase date 1234 10.2 2017-02-18 3453 18.9 2017-03-22 7689 8 2017-03-24 but when I'm passing the data

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.

Hemant's problem is that the indicators are not distributed uniformly. With a uniform distribution, categorization gives a reasonably optimal separation of cases. One approach would be to drop categorization and calculate the overall score as the mean of the standardized indicator scores. Whether this is an option I do not know. I did offer an "eyeball" set of breaks in a previous

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,

Hi Hemant, As I suspected, the code broke when I got to the line: result <- rfm_auto(df, id="user_id", payment ="subtotal_amount", date="created_at") Error in rfm_auto(df, id = "user_id", payment = "subtotal_amount", date = "cr eated_at") : could not find function "rfm_auto" It looks like you are using the hoxo-m/easyRFM

Hello Ulrik, Can you please explain this code means how and what this code is doing because I'm not able to understand it, if you can explain it i can use it in future by doing some Lil bit manipulation. Thanks data_help <- data_help %>% mutate(Purchase_ID = 1:n()) %>% group_by(Purchase_ID) %>% do(split_items(.)) cat_help %>% gather("Foo",

by using these two tables we have to create third table in this format where categories will be on the top and transaction will be in the rows, On 30 August 2017 at 16:42, Hemant Sain <hemantsain55 at gmail.com> wrote: > Hello Ulrik, > Can you please once check this code again on the following data set > because it doesn't giving same output to me due to absence of quantity,a

Hi Hemant, the solution is really quite similar, and the logic is identical: library(readr) library(dplyr) library(stringr) library(tidyr) data_help <- read_csv("data_help.csv") cat_help <- read_csv("cat_help.csv") # Helper function to split the Items and create a data_frame split_items <- function(items){ x <- items$Items_purchased_on_Receipts %>%

Hi You expect us to solve your problem but you ignore advice already recieved. Your data are unreadable, use dput(yourdata) instead. see ?dput > test<-read.table("clipboard", heade=T) Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : line 115 did not have 6 elements What is ?ideal interval? can you define it? Should it be such to provide eqal

Hey, i want to define 3 ideal breaks (bin) for each variable one of those variables is attached in the previous email, i don't want to consider quartile method because quartile is not working ideally for that data set because data distribution is non normal. so i want you to suggest another method so that i can define 3 breaks with the ideal interval for Recency, frequency and monetary to

Hello, I'm working on RFM analysis and i wanted to define my own breaks but my frequency distribution is not normally distributed so when I'm using quartile its not giving the optimal results. so I'm looking for a better approach where i can define breaks dynamically because after visualization i can do it easily but i want to apply this model so that it can automatically define the

I'm trying to perform an RFM analysis on the attached dataset, I'm able to get the results using the auto_rfm function but i want to define my own breaks for RFM. as follow r <-c(30,60,90) f <-c(2,5,8) m <-c(10,20,30) but when i tried to define my own breaks i got the identical result for RFM i.e 111 for every ID. please help me with this with working R script so that i can get

i have a vector containing values ranging from 0 to 24 i want to create another variable which can categorize those values like this please help me with an R code Thanks *Value New_Var*1 0 -5 3 0 -5 5 0 -5 9 6-10 7 6-10 5 6-10 4 0-5 11 11-15 12 11-15 18 16-20 23 21 -25 --

Hey PIKAL, It's not a homework neithe that is the real dataset i have signer NDA for my company so that i can share the original data file, Actually I'm working on a market basket analysis task but not able to convert my existing data table to appropriate format so that i can apply Apriori algorithm using R, and this is very important me to get it done because I'm an intern and if i

Hi Hemant, Let's take it one step at a time. Save this code as "qdrfm.R" in your R working directory: It includes the comments I added last time and fixes a bug in the recency scoring. 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))

Hi Your statement about attaching data is problematic. We cannot do much with it. Instead use output from dput(yourdata) to show us what exactly your data look like. We also do not know how do you want to split your data. It would be nice if you can show also what should be the bins with respective data. Unless you provide this information you probably would not get any sensible answer. Cheers

i want to do a market basket analysis and I?m trying to create a dataset for that i have two tables, one table contains daily transaction of products in which each row of table shows item purchased by the customer, The second table contains parent group under those products are fallen, for example under fruit category there are several fruits like mango, banana, apple etc. i want to create a third