How to organize a table?

I have a table around 700 rows and 7 columns. The second column is time. I have 5 different times. The last column is "cell type" which is an integer from 0 to 4. I need to know that at time=0 how many "cell type=3" exists? how many "cell type=4" exists? and do this for all times.

Is varfun appicable in this case?

Thanks

[madhan ravi]

Do not let the readers guess, so that they don't spend more time in guessing how the actual data looks like! Always post a sample data of what you're working with. You have always ignored the comments asking for the sample data until now! Posting pictures of data is completely pointless and useless. Attaching a file as .mat would be better to work with.

https://in.mathworks.com/matlabcentral/answers/6200-tutorial-how-to-ask-a-question-on-answers-and-get-a-fast-answer

[Zeynab Mousavikhamene]

@madhan ravi: I added a photo. If you track my question, I have added data to some of my questions.

[Andrei Bobrov]

Please read about varfun.

Answer 1

[Jon]

You could do this with a simple loop I'll assume your table is called mytable

% find maximum possible value for cell type
cellTypeMax = max(mytable.cell_type)
% find the row numbers of all the rows with time = 0
irow = mytable.time == 0
% loop through the rows at time zero counting number of each occurence
count = zeros(cellTypeMax,1); % preallocate
for k = 1:cellTypeMax
    count(k) = sum(mytable.cell_type(irow)==k)
end

You could also get fancier and eliminate the loop using histcounts (or histc in earlier versions)

% find maximum possible value for cell type
cellTypeMax = max(mytable.cell_type)
% find the row numbers of all the rows with time = 0
irow = mytable.time == 0

% define bin edges assume that cell types start at 1
edges = [0.5:1:cellTypeMax+1];

% count occurences within rows that are at time zero
count = histcounts(mytable.cell_type(irow),edges)

Answer 2

[Zeynab Mousavikhamene]

I used celltracker_group = varfun(@mean,celltracker,'GroupingVariables',{'time','cell_type'});

and it worked perfectly. It produces GroupCount which is exactly what I want.

Answer 3

[Andrei Bobrov]

T = readtable('img1.txt');

out = varfun(@sum,T,'GroupingVariables',...
        {'time','cell_type'},'InputVariables','cell_type');
out = out(:,1:end-1);

or

[A,out] = findgroups(T(:,{'time','cell_type'}));
out.counts = accumarray(A,1);