In a fairly recent (most recent?) version of MATLAB, you can do something like the following. First create some fake CSV files:
t1 = array2table(rand(10,2));
t2 = array2table(rand(10,2));
Now read them in and compute means and std devs. You don't give enough information, but perhaps something like this:
emptyTable = table(zeros(0,1),zeros(0,1));
Tout = table(strings(0,1),emptyTable,emptyTable,VariableNames=["File" "Mean" "Std"]);
for i = 1:length(xlFiles)
thisFile = xlFiles(i).name;
Tout.Mean(i,:) = mean(T);
end
Warning: The assignment added rows to the table, but did not assign values to all of the table's existing variables. Those variables are extended with rows containing default values.
Warning: The assignment added rows to the table, but did not assign values to all of the table's existing variables. Those variables are extended with rows containing default values.
Tout
Tout =
File Mean Std
________ __________________ __________________
Var1 Var2 Var1 Var2
_______ _______ _______ _______
"t1.csv" 0.38466 0.43901 0.28997 0.32914
"t2.csv" 0.35267 0.5149 0.23389 0.34535
Notice that I've just called mean and std on the tables. In earlier versions, you could not do that, so you'd need to do something like mean(T{:,:}) and pre-allocate Tout to contain 0x2 numeric matrices, not emptyTable.
