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  1. df1 <- orderData %>% 
  2.   group_by(member_no) %>% 
  3.   arrange(Year_month) %>% 
  4.   #Remove Instances where the same product appears repeatedly
  5.   distinct(member_no, category, .keep_all = TRUE) %>%
  6.   #Create Item ID Within Customer ID
  7.   mutate(item_id = row_number()) %>% 
  8.   select(member_no, Year_month, item_id, category) %>% 
  9.   ungroup() %>% 
  10.   #Convert Everything to Factor
  11.   mutate(across(.cols = c("member_no", "category"), .f = as.factor))
  12.  
  13. df1 <- df1[order(df1$member_no),] # descending order
  14.  
  15. # handle the special case where one person purchased multiple products on the same date  --------
  16. df2 <- df1
  17. # create unique id for each person-date pair
  18. df2$unique <- paste0(as.character(df2$member_no)," ", as.character(df2$Year_month)) 
  19. df2 <- df2 %>% 
  20.   # if a person purchased multiple products on the same date, 
  21.   # we need to merge these products into a basket like (A,B) on a single row
  22.   # otherwise, cspade will throw an error 
  23.   dplyr::group_by(unique) %>%
  24.   dplyr::summarise(product = paste(category, collapse = ","))
  25.  
  26. df2$member_no <- word(df2$unique, 1) # restore person id that was lost in the last step
  27. df2$Year_month <- word(df2$unique, 2)  # restore fill date that was lost in the last step
  28.  
  29. df2 <- df2 %>% 
  30.   group_by(member_no) %>% 
  31.   arrange(Year_month) %>% 
  32.   mutate(item_id = row_number()) %>% #Create Item ID Within person ID
  33.   select(member_no, Year_month, item_id, product) %>% 
  34.   ungroup()
  35.  
  36. df2 <- df2 %>% arrange(member_no)
  37.  
  38. save(df2,file="df2.Rda")
  39.  
  40. # c-spade pre-process -----------------------------------------------------
  41.  
  42. load("df2.Rda")
  43. df2$product <- factor(df2$product, levels = c('A', 'B', 'C'))
  44.  
  45. sessions <-  as(df2 %>% transmute(items = product), "transactions")
  46. transactionInfo(sessions)$sequenceID <- df2$member_no |> as.factor()
  47. transactionInfo(sessions)$eventID <- df2$item_id
  48. itemLabels(sessions) <- str_replace_all(itemLabels(sessions), "items=", "")
  49.  
  50. # cspade ------------------------------------------------------------------
  51.  
  52. itemsets <- cspade(sessions, 
  53.                    parameter = list(support = 0.0001), 
  54.                    control = list(verbose = FALSE))
  55.  
  56. inspect((itemsets))
  57.  
Success #stdin #stdout #stderr 0.25s 40884KB
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stdin 
Standard input is empty
stdout 
Standard output is empty
stderr 
Error: could not find function "%>%"
Execution halted
https://ideone.com/Vyef2M
language:
R (R 3.5.2)
created:
298 days ago
visibility:
secret

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