how to calculate Average of purchases of distinct items in the session using dplyr

Question: (Closed) how to calculate Average of purchases of distinct items in the session using dplyr

16 months ago by

I have a data frame with 3 columns: session id, item id and class. In the class column, 0 represents 'not purchased' and 1 represents 'purchased'.

> data
    session id        item id   class
      1                 1         0
      1                 1         0
      1                 1         0
      2                 1         1
      2                 2         0
      3                 1         0
      3                 0         1
      3                 3         1
      3                 2         0

I would like to to calculate the average number of purchases of distinct items for each unique session id. in SessionID 1 contain only one unique item and 0 purchase so avg is 0/1=0 session id 2 contain 1 purchase and 2 unique items so avg will be 1/2=0.5 and session id 3 contain 2 purchases and 4 unique items so avg will be 2/4=0.5. The results would look like this:

>  result   
session id       avg
   1             0/1=0
   2             0.5
   3             0.5

I have tried this till now:

data %>% group_by(session_id) %>% summarise(avg = ifelse(length(Class==1))/length(unique(item_id)))

but got the error:

Error in summarise_impl(.data, dots) : 
  Evaluation error: argument "yes" is missing, with no default.

dplyr R • 509 views

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modified 16 months ago • written 16 months ago by shameenkhan075 • 0

I don't see what this has to do with bioinformatics, you are better off asking at https://stackoverflow.com/

ADD REPLY • link modified 16 months ago • written 16 months ago by Benn ♦ 7.9k

Hello shameenkhan075!

We believe that this post does not fit the main topic of this site.

Not a bioinformatics question. Better ask https://stackoverflow.com/

For this reason we have closed your question. This allows us to keep the site focused on the topics that the community can help with.

If you disagree please tell us why in a reply below, we'll be happy to talk about it.

Cheers!

ADD REPLY • link written 16 months ago by Nicolas Rosewick ♦ 8.6k

:( ok .......................

ADD REPLY • link written 16 months ago by shameenkhan075 • 0

data session item class 1 1 1 0 2 1 1 0 3 1 1 0 4 2 1 1 5 2 2 0 6 3 1 0 7 3 0 1 8 3 3 1 9 3 2 0 aggregate(data[,3], by=data[1], FUN=mean) session x 1 1 0.0 2 2 0.5 3 3 0.5

require(dplyr) data %>% group_by(session) %>% summarise(mean(class)) # A tibble: 3 x 2 session `mean(class)` <dbl> <dbl> 1 1 0 2 2 0.5 3 3 0.5

itemsPerSession <- data.frame(data %>% group_by(session) %>% summarise(length(unique(item)))) itemsPerSession session length.unique.item.. 1 1 1 2 2 2 3 3 4 > countsPerSession <- data.frame(data %>% group_by(session) %>% summarise(sum(class))) countsPerSession session sum.class. 1 1 0 2 2 1 3 3 2 result <- data.frame( itemsPerSession[,1], ifelse( countsPerSession[,2] / itemsPerSession[,2] == 0, paste0(as.character(countsPerSession[,2]), "/", as.character(itemsPerSession[,2])), countsPerSession[,2] / itemsPerSession[,2] ) ) colnames(result) <- c("session id", "avg") result session id avg 1 1 0/1 2 2 0.5 3 3 0.5

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