Import_File.m

%- Import data from text file.
% Script for importing data from the following text file:
%
%    C:\Users\....
%
% To extend the code to different selected data or a different text file,
% generate a function instead of a script.

%- Initialize variables.
filename = 'E:\Archivos\Ejemplo.csv';
delimiter = ';';
startRow = 8;

%- Read columns of data as text:
% For more information, see the TEXTSCAN documentation.
formatSpec = '%s%s%s%s%s%[^\n\r]';

%- Open the text file.
fileID = fopen(filename,'r');

%- Read columns of data according to the format.
% This call is based on the structure of the file used to generate this
% code. If an error occurs for a different file, try regenerating the code
% from the Import Tool.
dataArray = textscan(fileID, formatSpec, 'Delimiter', delimiter, 'TextType', 'string', 'HeaderLines' ,startRow-1, 'ReturnOnError', false, 'EndOfLine', '\r\n');

%- Close the text file.
fclose(fileID);

%- Convert the contents of columns containing numeric text to numbers.
% Replace non-numeric text with NaN.
raw = repmat({''},length(dataArray{1}),length(dataArray)-1);
for col=1:length(dataArray)-1
    % raw(1:length(dataArray{col}),col) = mat2cell(dataArray{col}, ones(length(dataArray{col}), 1)); % Enable %
end
numericData = NaN(size(dataArray{1},1),size(dataArray,2));

for col=[2,3,4]
    % Converts text in the input cell array to numbers. Replaced non-numeric
    % text with NaN.
    rawData = dataArray{col};
    for row=1:size(rawData, 1)
        % Create a regular expression to detect and remove non-numeric prefixes and
        % suffixes.
        regexstr = '(?<prefix>.*?)(?<numbers>([-]*(\d+[\.]*)+[\,]{0,1}\d*[eEdD]{0,1}[-+]*\d*[i]{0,1})|([-]*(\d+[\.]*)*[\,]{1,1}\d+[eEdD]{0,1}[-+]*\d*[i]{0,1}))(?<suffix>.*)';
        try
            result = regexp(rawData(row), regexstr, 'names');
            numbers = result.numbers;
            
            % Detected commas in non-thousand locations.
            invalidThousandsSeparator = false;
            if numbers.contains('.')
                thousandsRegExp = '^\d+?(\.\d{3})*\,{0,1}\d*$';
                if isempty(regexp(numbers, thousandsRegExp, 'once'))
                    numbers = NaN;
                    invalidThousandsSeparator = true;
                end
            end
            % Convert numeric text to numbers.
            if ~invalidThousandsSeparator
                numbers = strrep(numbers, '.', '');
                numbers = strrep(numbers, ',', '.');
                numbers = textscan(char(numbers), '%f');
                %numericData(row, col) = numbers{1}; % enable %
                raw{row, col} = numbers{1};
            end
        catch
            raw{row, col} = rawData{row};
        end
    end
end

% Convert the contents of columns with dates to MATLAB datetimes using the
% specified date format.
try
    dates{1} = datetime(dataArray{1}, 'Format', 'dd/MM/yyyy', 'InputFormat', 'dd/MM/yyyy');
catch
    try
        % Handle dates surrounded by quotes
        %dataArray{1} = cellfun(@(x) x(2:end-1), dataArray{1}, 'UniformOutput', false); % enable %
        dates{1} = datetime(dataArray{1}, 'Format', 'dd/MM/yyyy', 'InputFormat', 'dd/MM/yyyy');
    catch
        dates{1} = repmat(datetime([NaN NaN NaN]), size(dataArray{1}));
    end
end

dates = dates(:,1);

%- Split data into numeric and string columns.
rawNumericColumns = raw(:, [2,3,4]);
rawStringColumns = string(raw(:, 5));


%- Replace non-numeric cells with NaN
%R = cellfun(@(x) ~isnumeric(x) && ~islogical(x),rawNumericColumns); % Find non-numeric cells % enable %
rawNumericColumns(R) = {NaN}; % Replace non-numeric cells

%- Create output variable
t2 = table;
t2.Fecha = dates{:, 1};
t2.Horas = cell2mat(rawNumericColumns(:, 1));
t2.Cuarto = cell2mat(rawNumericColumns(:, 2));
t2.Potencia = cell2mat(rawNumericColumns(:, 3));
t2.Calidad = rawStringColumns(:, 1);

% For code requiring serial dates (datenum) instead of datetime, uncomment
% the following line(s) below to return the imported dates as datenum(s).

% Ejemplo.Dia=datenum(Ejemplo.Dia);

%- Clear temporary variables
clearvars filename delimiter startRow formatSpec fileID dataArray ans raw col numericData rawData row regexstr result numbers invalidThousandsSeparator thousandsRegExp dates blankDates anyBlankDates invalidDates anyInvalidDates rawNumericColumns rawStringColumns R;

t2.Potencia=t2.Potencia/1000;