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    <p>Usually <code>textscan</code> and <code>regexp</code> is the way to go when parsing string fields (as shown <a href="https://stackoverflow.com/q/17818267/1336150#17819161">here</a>):</p> <ol> <li><p>Read the input lines as strings with <code>textscan</code>:</p> <pre><code>fid = fopen('input.px', 'r'); C = textscan(fid, '%s', 'Delimiter', '\n'); fclose(fid); </code></pre></li> <li><p>Parse the header field names and values using <code>regexp</code>. Picking the right regular expression should do the trick!</p> <pre><code>X = regexp(C{:}, '^\s*([^=\(\)]+)\s*=\s*"([^"]+)"\s*', 'tokens'); X = [X{:}]; %// Flatten the cell array X = reshape([X{:}], 2, []); %// Reshape into name-value pairs </code></pre></li> <li><p>The "VALUE" fields may span over multiple lines, so they need to be concatenated first:</p> <pre><code>idx_data = find(~cellfun('isempty', regexp(C{:}, '^\s*Data')), 1); idx_values = find(~cellfun('isempty', regexp(C{:}, '^\s*VALUES'))); Y = arrayfun(@(m, n){[C{:}{m:m + n - 1}]}, ... idx_values(idx_values &lt; idx_data), diff([idx_values; idx_data])); </code></pre> <p>... and then tokenized:</p> <pre><code>Y = regexp(Y, '"([^,"]+)"', 'tokens'); %// Tokenize values Y = cellfun(@(x){{x{1}{1}, {[x{2:end}]}}}, Y); %// Group values in one array Y = reshape([Y{:}], 2, []); %// Reshape into name-value pairs </code></pre></li> <li><p>Make sure the field names are legal (I've decided to convert everything to lowercase and replace apostrophes and any whitespace with underscores), and plug them into a struct:</p> <pre><code>X = [X, Y]; %// Store all fields in one array X(1, :) = lower(regexprep(X(1, :), '-+|\s+', '_')); S = struct(X{:}); </code></pre></li> </ol> <p>Here's what I get for your input file (only the header fields):</p> <pre><code>S = charset: 'ANSI' matrix: 'BE001' subject_code: 'BE' subject_area: 'Population' title: 'Population by region, time, marital status and sex.' month: {1x12 cell} region: {1x5 cell} </code></pre> <p>As for the data itself, it needs to be handled separately:</p> <ol> <li><p>Extract data lines after the "Data" field and replace all <code>".."</code> values with default values (say, <code>NaN</code>):</p> <pre><code>D = strrep(C{:}(idx_data + 1:end), '".."', 'NaN'); </code></pre> <p>Obviously this assumes that there are only numerical data after the "Data" field. However, this can be easily modified if this is not case.</p></li> <li><p>Convert the data to a numerical matrix and add it to the structure:</p> <pre><code>D = cellfun(@str2num, D, 'UniformOutput', false); S.data = vertcat(D{:}) </code></pre></li> </ol> <p>And here's <code>S.data</code> for your input file:</p> <pre><code>S.data = NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 24.80000 34.20000 52.00000 23.00000 NaN 32.10000 40.30000 50.70000 1.00000 NaN 31.60000 35.00000 49.10000 2.30000 41.20000 43.00000 50.80000 60.10000 0.00000 50.90000 52.00000 53.90000 65.90000 0.00000 </code></pre> <p>Hope this helps!</p>
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    1. USEitan T
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    1. COExcellent answer, Eitan T! Thank you very much for your help. I've been able to modify your suggested code to take care of a few other things I didn't mention in my original question. I was wondering if you could offer a second round of help regarding the Update that I made to the question. If you could take a look, that'd be great. Your help is very much appreciated.
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      1. USGraeme Walsh
    2. CO@GraemeWalsh Glad to help. How do you want the "values" field to be interpreted? That is, how should the corresponding field in the resulting structure look like?
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    3. COThanks for getting back to me, Eitan. Perhaps something like the following. S.month = 1976M01 1976M02 1976M03 1976M04 and so on... such that the output is an n x 1 column vector/matrix. For S.region =, the output could either be an n x 1 and 1 x n vector/matrix.
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