How to collapse session path data into from-to paths for visualizing network data?

Question

What are some ways to transform session path data such as this:

df
#   Session Link1 Link2 Link3 Link4 Link5
# 1       1     A     B                  
# 2       2     C                        
# 3       3     D     A     B            
# 4       4     C     F     G     H     J
# 5       5     A     B     C            

Into a data set that looks like this:

desired
#    Session From   To
# 1        1    A    B
# 2        2    C <NA>
# 3        3    D    A
# 4        3    A    B
# 5        4    C    F
# 6        4    F    G
# 7        4    G    H
# 8        4    H    J
# 9        5    A    B
# 10       5    B    C

Data for reproducibility:

df <- structure(list(Session = 1:5, Link1 = structure(c(1L, 2L, 3L, 2L, 1L), .Label = c("A", "C", "D"), class = "factor"), Link2 = structure(c(3L, 1L, 2L, 4L, 3L), .Label = c("", "A", "B", "F"), class = "factor"), Link3 = structure(c(1L, 1L, 2L, 4L, 3L), .Label = c("", "B", "C", "G"), class = "factor"), Link4 = structure(c(1L, 1L, 1L, 2L, 1L), .Label = c("", "H"), class = "factor"), Link5 = structure(c(1L, 1L, 1L, 2L, 1L), .Label = c("", "J"), class = "factor")), .Names = c("Session", "Link1", "Link2", "Link3", "Link4", "Link5"), class = "data.frame", row.names = c(NA, -5L))
desired <- structure(list(Session = c(1L, 2L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L), From = structure(c(1L, 3L, 4L, 1L, 3L, 5L, 6L, 7L, 1L, 2L), .Label = c("A", "B", "C", "D", "F", "G", "H"), class = "factor"), To = structure(c(2L, NA, 1L, 2L, 4L, 5L, 6L, 7L, 2L, 3L), .Label = c("A", "B", "C", "F", "G", "H", "J"), class = "factor")), .Names = c("Session", "From", "To"), class = "data.frame", row.names = c(NA, -10L))

Answer 1

We could use data.table. Convert the 'data.frame' to 'data.table' (setDT(df)). Reshape from 'wide' to 'long' format with melt specifying the id.var as 'Session'. Remove the 'value' elements that are empty [value!='']. Grouped by 'Session', we insert 'NA' values in the 'value' column for those 'Session' that have only a single row (if...else), create a two columns ('From' and 'To') by removing the last and first element of 'V1' grouped by 'Session'.

 library(data.table)#v1.9.5+
 melt(setDT(df), id.var='Session')[value!=''][, 
   if(.N==1L) c(value, NA) else value, by = Session][,
      list(From=V1[-.N], To=V1[-1L]), by = Session]
 #   Session From To
 #1:       1    A  B
 #2:       2    C NA
 #3:       3    D  A
 #4:       3    A  B
 #5:       4    C  F
 #6:       4    F  G
 #7:       4    G  H
 #8:       4    H  J
 #9:       5    A  B
 #10:      5    B  C

The above could be simplified to a single block after the melt step. For some reason, tmp[-.N] is not working. So I used tmp[1:(.N-1)].

melt(setDT(df), id.var= 'Session')[value!='', {
              tmp <- if(.N==1L) c(value, NA) else value
              list(From= tmp[1:(.N-1)], To= tmp[-1L]) }, by = Session]
#    Session From To
#1:       1    A  B
#2:       2    C NA
#3:       3    D  A
#4:       3    A  B
#5:       4    C  F
#6:       4    F  G
#7:       4    G  H
#8:       4    H  J
#9:       5    A  B
#10:      5    B  C