function [] = FitColumn(filename)
%FitColumn Find the best fitting second order exponential function for
%dataset
%   read in dataset and then for each rocof column determine exponential
%   fit that best fits the event data.
    [~, name, ~] = fileparts(filename);
    rocof_ds = datastore(filename, 'TreatAsMissing', 'NA');
   
    
    rocof_data = readall(rocof_ds);
    rocof_data = rmmissing(rocof_data); % ensure data for all columns
    rocof_data = table2array(rocof_data);
   
    
    % for each PMU column
    tab = zeros(3,4);
    for ii = 1:3
        jj = ii*10 + 1;  % skip time column
        filtered_data = FilterData(rocof_data(:,jj));      
      
        [start_t, stop_t] = FindEventPeriod(filtered_data);
        [exp_coeff, exp_func] = DecayFit(filtered_data(start_t:stop_t));

        for kk = 1:length(exp_coeff)
           tab(ii,kk) = exp_coeff(kk); 
        end

        fig = figure('units', 'inches', 'papersize', [8,8]);
        subplot(1,1,1);
        hold on
        plot(rocof_data(start_t:stop_t,jj))
        plot(exp_func)
        hold off

        %subplot(1,2,2);
        %hold on
        %plot(rocof_data(:,jj))
        %plot(filtered_data)
        %hold off
        print(fig,...
            strcat("..\plots\",name, int2str(ii)), '-dpdf', '-fillpage');
    end

    T = array2table(tab);
    T.Properties.VariableNames = {'etta', 'Wn', 'A', 'GoF'};
    writetable(T, "..\output\" + name + "_coeff.csv");
end