Import CSV file with mixed data types

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眼角桃花
眼角桃花 2020-11-27 04:13

I\'m working with MATLAB for few days and I\'m having difficulties to import a CSV-file to a matrix.

My problem is that my CSV-file contains almost only Strings and

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  •  难免孤独
    2020-11-27 05:05

    For the case when you know how many columns of data there will be in your CSV file, one simple call to textscan like Amro suggests will be your best solution.

    However, if you don't know a priori how many columns are in your file, you can use a more general approach like I did in the following function. I first used the function fgetl to read each line of the file into a cell array. Then I used the function textscan to parse each line into separate strings using a predefined field delimiter and treating the integer fields as strings for now (they can be converted to numeric values later). Here is the resulting code, placed in a function read_mixed_csv:

    function lineArray = read_mixed_csv(fileName, delimiter)
    
      fid = fopen(fileName, 'r');         % Open the file
      lineArray = cell(100, 1);           % Preallocate a cell array (ideally slightly
                                          %   larger than is needed)
      lineIndex = 1;                      % Index of cell to place the next line in
      nextLine = fgetl(fid);              % Read the first line from the file
      while ~isequal(nextLine, -1)        % Loop while not at the end of the file
        lineArray{lineIndex} = nextLine;  % Add the line to the cell array
        lineIndex = lineIndex+1;          % Increment the line index
        nextLine = fgetl(fid);            % Read the next line from the file
      end
      fclose(fid);                        % Close the file
    
      lineArray = lineArray(1:lineIndex-1);              % Remove empty cells, if needed
      for iLine = 1:lineIndex-1                          % Loop over lines
        lineData = textscan(lineArray{iLine}, '%s', ...  % Read strings
                            'Delimiter', delimiter);
        lineData = lineData{1};                          % Remove cell encapsulation
        if strcmp(lineArray{iLine}(end), delimiter)      % Account for when the line
          lineData{end+1} = '';                          %   ends with a delimiter
        end
        lineArray(iLine, 1:numel(lineData)) = lineData;  % Overwrite line data
      end
    
    end
    

    Running this function on the sample file content from the question gives this result:

    >> data = read_mixed_csv('myfile.csv', ';')
    
    data = 
    
      Columns 1 through 7
    
        '04'    'abc'    'def'    'ghj'    'klm'    ''            ''        
        ''      ''       ''       ''       ''       'Test'        'text'    
        ''      ''       ''       ''       ''       'asdfhsdf'    'dsafdsag'
    
      Columns 8 through 10
    
        ''          ''    ''
        '0xFF'      ''    ''
        '0x0F0F'    ''    ''
    

    The result is a 3-by-10 cell array with one field per cell where missing fields are represented by the empty string ''. Now you can access each cell or a combination of cells to format them as you like. For example, if you wanted to change the fields in the first column from strings to integer values, you could use the function str2double as follows:

    >> data(:, 1) = cellfun(@(s) {str2double(s)}, data(:, 1))
    
    data = 
    
      Columns 1 through 7
    
        [  4]    'abc'    'def'    'ghj'    'klm'    ''            ''        
        [NaN]    ''       ''       ''       ''       'Test'        'text'    
        [NaN]    ''       ''       ''       ''       'asdfhsdf'    'dsafdsag'
    
      Columns 8 through 10
    
        ''          ''    ''
        '0xFF'      ''    ''
        '0x0F0F'    ''    ''
    

    Note that the empty fields results in NaN values.

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