Fastest way to import CSV files in MATLAB

Question

I've written a script that saves its output to a CSV file for later reference, but the second script for importing the data takes an ungainly amount of time to read it back in.

The data is in the following format:

Item1,val1,val2,val3
Item2,val4,val5,val6,val7
Item3,val8,val9

where the headers are on the left-most column, and the data values take up the remainder of the row. One major difficulty is that the arrays of data values can be different lengths for each test item. I'd save it as a structure, but I need to be able to edit it outside the MATLAB environment, since sometimes I have to delete rows of bad data on a computer that doesn't have MATLAB installed. So really, part one of my question is: Should I save the data in a different format?

Second part of the question: I've tried importdata, csvread, and dlmread, but I'm not sure which is best, or if there's a better solution. Right now I'm using my own script using a loop and fgetl, which is horribly slow for large files. Any suggestions?

function [data,headers]=csvreader(filename); %V1_1
 fid=fopen(filename,'r');
 data={};
 headers={};
 count=1;
 while 1
      textline=fgetl(fid);
      if ~ischar(textline),   break,   end
      nextchar=textline(1);
      idx=1;
      while nextchar~=','
        headers{count}(idx)=textline(1);
        idx=idx+1;
        textline(1)=[];
        nextchar=textline(1);
      end
      textline(1)=[];
      data{count}=str2num(textline);
      count=count+1;
 end
 fclose(fid);

(I know this is probably terribly written code - I'm an engineer, not a programmer, please don't yell at me - any suggestions for improvement would be welcome, though.)

Answer 1

It would probably make the data easier to read if you could pad the file with NaN values when your first script creates it:

Item1,1,2,3,NaN
Item2,4,5,6,7
Item3,8,9,NaN,NaN

or you could even just print empty fields:

Item1,1,2,3,
Item2,4,5,6,7
Item3,8,9,,

Of course, in order to pad properly you would need to know what the maximum number of values across all the items is before hand. With either format above, you could then use one of the standard file reading functions, like TEXTSCAN for example:

>> fid = fopen('uneven_data.txt','rt');
>> C = textscan(fid,'%s %f %f %f %f','Delimiter',',','CollectOutput',1);
>> fclose(fid);
>> C{1}

ans = 

    'Item1'
    'Item2'
    'Item3'

>> C{2}

ans =

     1     2     3   NaN  %# TEXTSCAN sets empty fields to NaN anyway
     4     5     6     7
     8     9   NaN   NaN