# Data visualization of frequencies of state transitions (possibly in R?)

I am working on some experimental data, which can be of types A, B and C. Now I observe this data for 5 time points, and I can see them move between A to B, B to C,... etc. I see such transitions for a number of independent data points, and I have the cumulative frequencies from all data.

For example, I have: $$Period A B C \newline 1 4 4 2 2 1 2 7 3 0 1 9 4 10 0 0 5 8 1 1$$

I DO know the transitions from one state to another, for example from A->B, B->C so on and so forth. For example I know that from Period 1, (all A's went to C. Among the missing B's one went to A, and rest to C.) I was thinking of what would be the best way to visually represent this time wise transitions from one state to another. I was thinking that there might be some better way than just having a transition matrix, maybe something that looks like a Markov Chain but which could accommodate all the 5 periods of transitions in a succinct way? I myself work on a statistical software called STATA, which has limited graphical applications. IS there something on other software packages (R maybe?) which can help me in this?

• Sorry for the hack representation of the data matrix.
• Is the first line correct or should that also add up to 10? And is my understanding correct that for example in line 3 you don't know where the singleton B came from? Apr 19 '16 at 7:42
• I'm not clear on your data, so its hard to suggest solution. I understand you have 5 "snapshots in time". So do you have, say 20 items that you are observing and from the first line, 4 are in state A, 4 are in state B, 3 are in state C? Then for period 2, only 1 is in state A, 2 are in state B and 7 in state C? If this is true, do you have more granular data? do you know the order that states change from and to, is the state transition matrix well established. Apr 19 '16 at 11:16
• @JanvanderVegt Yes, I will edit to make it add up to 10. Also, I DO know what transitions where, so I know the flow from A->B, B->C etc Apr 19 '16 at 18:43
• This post I made in stack overflow some time ago may be of interest to you: stackoverflow.com/questions/32633507/… Apr 19 '16 at 21:14
• What sort of analysis do you want to do in the end? I have an idea, but it could be completely off track, depending on what analysis you are doing. Apr 19 '16 at 21:15

How about a Sankey diagram with time on the x-axis and flow width representing state transition frequency. Here is a SO discussion on implementing Sankey diagrams in R. One possible R package is {riverplot}... here is code showing the first transition in your data:

library(riverplot)
nodes <- as.character(sapply(1:2, FUN = function(n){paste0(LETTERS[1:3],n)}))
edges <- list(A1=list(C2=4), B1=list(A2=1,C2=1,B2=2), C1=list(C2=2))
r <- makeRiver( nodes, edges, node_xpos= c( 1,1,1 ,2,2,2),
node_labels= c( A1= "A", B1= "B", C1= "C", A2="A",B2="B",C2="C" ))
plot( r )


Will produce this: If you have the data in the form of a table of transition counts: $$Transition Period 1 Period 2 Period 3 Period 4 \newline A->A 0 0 0 8 A->B 0 0 0 1 A->C 4 1 0 1 B->A 1 0 1 0 B->B 2 0 0 0 B->C 1 1 0 0 C->A 0 0 9 0 C->B 0 0 0 0 C->C 2 7 0 0$$ Then a possible visualization is an area plot. The following chart was produceds in Excel (use Charts/Area button on the Insert ribbon). This chart accurately captures all transitions that occurred in each period. Shaded areas of different colors represent the relative frequencies of transitions by origin-destination pair. • This looks very promising! Could you kindly tell me what software+command you used to generate this, and help me in how to read the plot. For example, what does the orange/ green band mean? Apr 22 '16 at 0:16
• I have added more detail to my answer. Apr 22 '16 at 1:45

I'm not sure if this is the type of analysis you are after, but you mention that the visual side is restricted in STATA. A colleague wrote a blog that utilised neo4j to read web data into a graph database, and d3js to display the data graphically.

I realise you don't have web data as such, but your data can be stored in a graph database, but I guess when I was asking about what types of analysis you were planning on doing, I was asking were you needing a qualitative or quantitative direction. But it seems like you are still in the process of working that out. The nice thing with neo4j is that you can pull the data into R and do any sort of analytics you want on it.

• I am not looking for a quantitative or qualitative direction per se. I would know what to do with the data, and what regressions to run. I am looking for a good way to show graphically how the state transitions differ across treatments. For example, Tguzella's comment on my post is the closest I have received to what I am looking for. Apr 20 '16 at 18:18
• I'd certainly look at my suggestion of neo4j/d3js then, as it will show graphically how your various states differ. Apr 20 '16 at 18:26