How to put multiple elements in a cell?

I am loading in a mat file that contains a 6 X 191 cell (contains pixels).

*I am not able to upload a zip file of the mat file because of the size so I took a screenshot.

I want to calculate the mean, medican, std, skewness, and kurtosis for each column.

Then I want to take each of the column's statistic and put it in a array with 5x1 elements in each cell. (1 x 191 cell array with 5 elements in each cell)

Is that possible? In the future, I want to make a for loop out of this, so I can go through multiple mat files.

I have this code so far.

I tried using the vertcat and I ended up getting a 5 X 191 double (i don't know if it turned to a matrix).

% lead feats.mat
load('Feats.mat');

% calculate various statistics per column
feat_mean = arrayfun(@(k) mean([featints{1,k} ; featints{2,k}]), 1:size(featints,2));
feat_med = arrayfun(@(k) median([featints{1,k} ; featints{2,k}]), 1:size(featints,2));
feat_std = arrayfun(@(k) std([featints{1,k} ; featints{2,k}]), 1:size(featints,2));
feat_skw = arrayfun(@(k) skewness([featints{1,k} ; featints{2,k}]), 1:size(featints,2));
feat_kurt = arrayfun(@(k) kurtosis([featints{1,k} ; featints{2,k}]), 1:size(featints,2));

% combine all the stats into different rows
combine_feat_stat = vertcat(feat_mean, feat_med, feat_std, feat_skw, feat_kurt);

% 5X1 elements in each cell

Answer 1

[KSSV]

Let A be your 6*191 cell array.

[m,n] = size(A) ; 
M = zeros(1,n) ;   % initialize mean 
for i = 1:n
    C = cell2mat(A(:,i)) ;  % convers the first column of cells into array 
    M(i) = mean(C) ; 
end

[Nandini Chatterjee]

Thank you but I don't think that will help with the 5x1 cell in each cell. Instead I get a class type of double [#;#;#;#;#]. How can I fix this?

I want this in the end,

Not this,

% lead feats.mat
load('Feats.mat');

% calculate various statistics per column
[m,n] = size(featints); 
feat_mean = zeros(1,n);   % initialize mean 
feat_med = zeros(1,n);    % initialize median
feat_std = zeros(1,n);    % initialize standard deviation
feat_skw = zeros(1,n);    % initialize skewness
feat_kurt = zeros(1,n);   % initialize kurtosis
for i = 1:n
    C = cell2mat(featints(:,i));  % convert the first column of cells into array 
    feat_mean(i) = mean(C);
    feat_med(i) = median(C);
    feat_std(i) = std(C);
    feat_skw(i) = skewness(C);
    feat_kurt(i) = kurtosis(C);
end

% combine all the stats into different rows
combine_feat_stat = vertcat(feat_mean, feat_med, feat_std, feat_skw, feat_kurt);
out = num2cell(combine_feat_stat,1);

% 5x1 elements in each cell [1xn cell array]
feat_statistics = num2cell(out,1);
feat_stats = {};
for k1 = 1:length(feat_statistics)
    if ~isempty(feat_statistics{k1})
        feat_stats = horzcat(feat_stats, feat_statistics{k1});
    end
end