Pulling Pairs of Factors from a within a list into a 2-column dataframe in R

Question

I'm new to r and am trying to put pairs of factors that are side by side in a list into a dataframe so that I can export them as edges for GEPHI. I am trying to create a dataset that acts like a shopping list for each individual users journey where each edge would be a journey from one shopping point to another.

Here is sample data that I am testing on:

a <- c("a","a","a","b","b","a","a","b","a","a","c","d","c")
b <- c(12,22,44,22,33,55,33,66,88,55,33,66,77)
a1 <- data.frame(a,b)
b1 <- tapply(a1$b, a1$a, list)

Which looks like this:

$a
[1] 12 22 44 55 33 88 55

$b
[1] 22 33 66

$c
[1] 33 77

$d
[1] 66

Hence, "$a, $b, $c, $d" would be individual users and the lists within would be there transaction journeys. I want the first row to be "12 22" then second be "22 44"... ect with the last being "33 77".

So far I have created the function called "pairsfunction" and have tried to use lapply with it but it doesn't seem to work.

Here is what I have so far:

pairingfunction <- function(x) {
  pairdf <- data.frame()
  for (i in 1:(length(x)-1)){  
    a <- x[i] 
    b <- x[(i+1)]
    pairdf[(nrows(pairdf)+1)] <- a
    pairdf[(nrows(pairdf))] <- b
  } return(pairdf)
}

lapply(b1, pairingfunction)

If someone could help fix the function or let me know a better way than using lapply that would be fantastic. Thanks

Answer 1

You can shift and cbind the list elements. Wrap this in lapply to do it for each element in your list. You can wrap it in do.call(rbind, ...) to get it in matrix form.

do.call(rbind, lapply(b1, function(x) cbind(x[-length(x)], x[-1])))

Answer 2

You could leverage the nest() function from the tidyr package:

library(tidyr)
library(dplyr)

a <- c("a","a","a","b","b","a","a","b","a","a","c","d","c")
b <- c(12,22,44,22,33,55,33,66,88,55,33,66,77)
df <- data.frame(user = a, touchpoint = b)

df %>% nest(touchpoint)

#   user                       data
# 1    a 12, 22, 44, 55, 33, 88, 55
# 2    b                 22, 33, 66
# 3    c                     33, 77
# 4    d                         66