# Machine Learning onramp section 4.6

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AG on 7 Jun 2020
Answered: Asvin Kumar on 10 Jun 2020
Having trouble with the further practice section:
1. how can i have the for loop iterate through all the variables in the sampleletters.mat file without creating an array of them manually?
2. can i concatenate these results of the new function 'extract' without first creating a table outside of the for loop?
3. how do i vertically concatenate outputs of extract? when i use either a semicolon (as shown) or [ ] , i get the error 'all tables being horizontally concatenated must have the same number of rows.'
screenshots of the question and my current work below!

Asvin Kumar on 10 Jun 2020
Since the outputs of extract are already tables you can concatenate them without creating an empty table.
For 1, you could approach it in a slightly different manner:
T = whos('-file','sampleletters.mat');
BigTable = extract(T(1).name);
for i = 2:size(T,1)
BigTable = [BigTable ; extract(T(i).name)];
end
BigTable
function feat = extract(var_name)
aratio = range(letter.Y)/range(letter.X);
idxmin = islocalmin(letter.X,"MinProminence",0.1);
numXmin = nnz(idxmin);
idxmax = islocalmax(letter.Y,"MinProminence",0.1);
numYmax = nnz(idxmax);
dT = diff(letter.Time);
dXdT = diff(letter.X)./dT;
dYdT = diff(letter.Y)./dT;
avgdX = mean(dXdT,"omitnan");
avgdY = mean(dYdT,"omitnan");
corrXY = corr(letter.X,letter.Y,"rows","complete");
featurenames = ["AspectRatio","NumMinX","NumMinY","AvgU","AvgV","CorrXY"];
feat = table(aratio,numXmin,numYmax,avgdX,avgdY,corrXY,'VariableNames',featurenames);
end