How to find streaks in a categorical vector?

1 view (last 30 days)
Hi,
is there a way to identify streaks in a categorical vector? Considering number vectors, I've found out that it might be useful to work with the functions find and diff but as this problem is concerned with a categorical vector, this does not work. Is there a workaround or would I need to convert my categorical vector into a number vector?
Many thanks for your help!
The table below illustrates my plan:
+--------+--------+
| CatVec | SerVec |
+--------+--------+
| A | 1 |
+--------+--------+
| C | 1 |
+--------+--------+
| A | 1 |
+--------+--------+
| B | 1 |
+--------+--------+
| B | 2 |
+--------+--------+
| C | 1 |
+--------+--------+
| A | 1 |
+--------+--------+
| A | 2 |
+--------+--------+
| A | 3 |
+--------+--------+
| B | 1 |
+--------+--------+
| C | 1 |
+--------+--------+
| C | 2 |
+--------+--------+
  2 Comments
Image Analyst
Image Analyst on 30 Apr 2020
Did you look at the findgroups() function?
Ameer Hamza
Ameer Hamza on 30 Apr 2020
To easily solve this problem, It will be much easier to use double datatype as compared to categorical. You can simply use double() to convert the categorical array to the double array.

Sign in to comment.

Accepted Answer

Peter Perkins
Peter Perkins on 5 May 2020
diff is a numeric function. categorical is not numeric. Ordinal categoricals have a mathematical ordering, but they don't have a "distance", so diff makes no sense for them.
But diff(x) is just x(2:end) - x(1:end-1). Again, categorical isn't numeric, but remember, the "trick" is not just diff(x), it's diff(x) > 0, so what you want is
d = c(2:end) ~= c(1:end-1)
At that point, you are exactly where you'd be if you had started with a numeric vector. Your runs (including singleton runs) begin at find(d) and the run lengths are diff(find(d)).

More Answers (1)

Vimal Rathod
Vimal Rathod on 5 May 2020
You can use "findgroups" function to make groups in Categorical Data. The function accepts the data as categorical data so you don't need to change your data.
Refer to the following link to know more about the function.

Categories

Find more on Statistics and Machine Learning Toolbox in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!