I have gathered a set of transactions in a CSV file of the format:
{Pierre, lait, oeuf, beurre, pain}
{Paul, mange du pain,jambon, lait}
{Jacques, oeuf, va chez la crémière, pain, voiture}
I plan to do a simple association rule analysis, but first I want to exclude items from each transactions which do not belong to ReferenceSet = {lait, oeuf, beurre, pain}
.
Thus my resulting dataset would be, in my example :
{Pierre, lait, oeuf, beurre, pain}
{Paul,lait}
{Jacques, oeuf, pain,}
I'm sure this is quite simple, but would love to read suggestions/answers to help me a bit.
Another answer references %in%
, but in this case intersect
is even handier (you may want to look at match
, too -- but I think it's documented in the same place as %in%
) -- with lapply
and intersect
we can make the answer into a one-liner:
Data:
> L <- list(pierre=c("lait","oeuf","beurre","pain") ,
+ paul=c("mange du pain", "jambon", "lait"),
+ jacques=c("oeuf","va chez la crémière", "pain", "voiture"))
> reference <- c("lait", "oeuf", "beurre", "pain")
Answer:
> lapply(L,intersect,reference)
$pierre
[1] "lait" "oeuf" "beurre" "pain"
$paul
[1] "lait"
$jacques
[1] "oeuf" "pain"
One way is follows (but, as I'm leaving the structure as a matrix I've left NAs where data has been removed (these could be removed if exporting back to CSV); I'm also sure it's possible to do it without loops - this would make it faster (but, IMHO less readable), and I'm sure there's a more efficient way to do the logic too - I'd also be interested in seeing someone's else view on this)
ref <- c("lait","oeuf","beurre","pain")
input <- read.csv("info.csv",sep=",",header=FALSE,strip.white=TRUE)
> input
V1 V2 V3 V4 V5
1 Pierre lait oeuf beurre pain
2 Paul mange du pain jambon lait
3 Jacques oeuf va chez la crémière pain voiture
input <- as.matrix(input)
output <- matrix(nrow=nrow(input),ncol=ncol(input))
currentRow <- c()
for(i in 1:nrow(input)) {
j <- 2
output[i,1]<-input[i,1]
for(k in 2:length(input[i,])) {
if(toString(input[i,k]) %in% ref){
output[i,j] <- toString(input[i,k])
j<-j+1
}
}
}
> output
[,1] [,2] [,3] [,4] [,5]
[1,] "Pierre" "lait" "oeuf" "beurre" "pain"
[2,] "Paul" "lait" NA NA NA
[3,] "Jacques" "oeuf" "pain" NA NA
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With