I have a data in the following form :
CIN TRN_TYP
9079954    1
9079954    2
9079954    3
9079954    4
9079954    5
9079954    4
9079954    5
9079954    6
9079954    7
9079954    8
9079954    9
9079954    9
.                    .
.                    .
.                    .
there are 100 types of CIN (9079954,12441087,15246633,...) and respective
TRN_TYP

first of all, I want this data to be grouped into basket format:
9079954   1, 2, 3, 4, 5, ....
12441087  19, 14, 21, 3, 7, ...
.
.
.
and then apply eclat from arules package to find frequent patterns.

1) I ran the following code:
file<-read.csv("D:/R/Practice/Data_Input_NUM.csv")
file <- file[!duplicated(file),]
eclat(split(file$TRN_TYP,file$CIN))

but it gave me the following error:
Error in asMethod(object) : can not coerce list with transactions with
duplicated items

2) I ran this code:
file<-read.csv("D:/R/Practice/Data_Input_NUM.csv")
file_new<-file[,c(3,6)] # because my file Data_Input_NUM has many other
columns as well, so I selecting only CIN and TRN_TYP
file_new <- file_new[!duplicated(file_new),]
eclat(split(file_new$TRN_TYP,file_new$CIN))

but again:
Error in eclat(split(file_new$TRN_TYP, file_new$CIN)) :
  internal error in trio library

PLEASE HELP

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