How to group statistics by 2 variables for plotting?

Hi,

I am exploring the statistics of some clustering. I have an output cell array 'VolcRegion_Clust.mat' with the region (8 different regions) of each record, and which of the 10 clusters it has been assigned to. I am trying to extract statistics for the number of records in each cluster (1-10), grouped by the region. I have tried extensively using loops, tables and other methods to split or summarise the data accordingly (without usings 100s of lines splitting each region/cluster combination individually), but have had no luck so far. Any hints or help would be appreciated - thank you.

Below is a chart made with sample data in excel ('Group_Test.xlsx') illustrating the sort of output I am hoping to get to in the final product.

Answer 1

[J. Alex Lee]

are you looking for something like this?

load("VolcRegion_clust.mat")

T = cell2table(VolcType_clust,"VariableNames",["Region","Cluster"]);
T.Region = categorical(T.Region)

T = 66×2 table
                Region                Cluster
    ______________________________    _______

    Alaska                               5   
    South America                        2   
    Alaska                               2   
    Alaska                               2   
    Iceland and Arctic Ocean             2   
    Alaska                               2   
    Alaska                               2   
    Alaska                               2   
    Alaska                               2   
    Alaska                               2   
    Alaska                               2   
    Iceland and Arctic Ocean            10   
    Mediterranean and Western Asia       2   
    México and Central America           2   
    South America                        2   
    South America                        2   

GS = groupsummary(T,["Region","Cluster"])

GS = 19×3 table
                Region                Cluster    GroupCount
    ______________________________    _______    __________

    Africa and Red Sea                   2            3    
    Alaska                               2           22    
    Alaska                               5            1    
    Atlantic Ocean                       2            2    
    Canada and Western USA               2            6    
    Canada and Western USA               5            1    
    Canada and Western USA               7            1    
    Iceland and Arctic Ocean             1            2    
    Iceland and Arctic Ocean             2            5    
    Iceland and Arctic Ocean            10            1    
    Mediterranean and Western Asia       2            2    
    México and Central America           2            1    
    México and Central America           9            1    
    South America                        2           12    
    South America                        3            1    
    South America                        4            1    

Data = unstack(GS,"GroupCount","Region");

Warning: Table variable names that were not valid MATLAB identifiers have been modified. Since table variable names must be unique, any table variable names that happened to match the new identifiers also have been modified.
To use the original INDVAR values as table variable names, set 'VariableNamingRule' to 'preserve'.

Data = sortrows(Data,"Cluster")

Data = 10×9 table
    Cluster    AfricaAndRedSea    Alaska    AtlanticOcean    CanadaAndWesternUSA    IcelandAndArcticOcean    MediterraneanAndWesternAsia    M_xicoAndCentralAmerica    SouthAmerica
    _______    _______________    ______    _____________    ___________________    _____________________    ___________________________    _______________________    ____________

       1             NaN           NaN           NaN                 NaN                       2                         NaN                          NaN                  NaN     
       2               3            22             2                   6                       5                           2                            1                   12     
       3             NaN           NaN           NaN                 NaN                     NaN                         NaN                          NaN                    1     
       4             NaN           NaN           NaN                 NaN                     NaN                         NaN                          NaN                    1     
       5             NaN             1           NaN                   1                     NaN                         NaN                          NaN                    2     
       6             NaN           NaN           NaN                 NaN                     NaN                         NaN                          NaN                    1     
       7             NaN           NaN           NaN                   1                     NaN                         NaN                          NaN                  NaN     
       8             NaN           NaN           NaN                 NaN                     NaN                         NaN                          NaN                    1     
       9             NaN           NaN           NaN                 NaN                     NaN                         NaN                            1                  NaN     
      10             NaN           NaN           NaN                 NaN                       1                         NaN                          NaN                  NaN     

Labels = unique(VolcType_clust(:,1));
figure(1)
bar(categorical(Data.Cluster),Data{:,2:end},'stacked')
legend(Labels)

[Ben]

That's great, thanks! The main thing I wasn't aware of was the 'unstack' function, which is really useful! For anyone on this thread wondering how to then plot this up as a stacked bar, my code is below (add this below J's code):

Labels = unique(VolcType_clust(:,1));

figure(1)
bar(categorical(Data.Cluster),Data{:,2:end},'stacked')
legend(Labels)

[J. Alex Lee]

@Ben, I appended your code to show the whole thing.

Yea, unstack/stack are ones that I vaguely understand, but never fully understood the arguments - I usually have to experiment :)