Products & Services Solutions Academia Support User Community Company

Learn more about MATLAB   

Importing Text Data Files

The easiest way to import data from an ASCII file is to use the Import Wizard, a graphical user interface.

For most files, the Import Wizard and importdata automatically detect:

For example, you can easily read ASCII data in the following form (see Importing Numeric ASCII Data with Headers):

Requirements for the Import Wizard or importdata

The data in your file must be:

If your data file does not meet these requirements, consider using textscan. For more information, see:

To import files with more complex formats, see Importing Text Data Files with Low-Level I/O.

Importing a Subset of Your Data

The Import Wizard and importdata import all rows and columns of your data file.

To import only part of your data, use dlmread or textscan.

Back to Top

Importing Numeric ASCII Data

You can import any ASCII data file with numeric fields easily using the Import Wizard or importdata. For example, consider a comma-delimited ASCII data file named ph.dat:

7.2, 8.5, 6.2, 6.6
5.4, 9.2, 8.1, 7.2

Use importdata to import the data. Call whos to learn the class of the data returned, and type the name of the output variable (in this case, 'ph') to see its contents:

ph = importdata('ph.dat');

whos ph

Name             Size            Bytes  Class     Attributes
  ph             2x4                64  double              

ph

ph = 
    7.2000    8.5000    6.2000    6.6000
    5.4000    9.2000    8.1000    7.2000

Selecting a Range of Numeric Data

To select specific rows and columns to import, use dlmread. For example, to read the first two columns from ph.dat:

ph_partial = dlmread('ph.dat', ',', 'A1..B2')

ph_partial = 
    7.2000    8.5000
    5.4000    9.2000

Importing Formatted Dates and Times

Formatted dates and times (such as '01/01/01' or '12:30:45') are not numeric fields. How you import them depends on their location in the file. If the dates and times are:

Back to Top

Importing Numeric ASCII Data with Headers

You can import any ASCII data file with numeric fields and text headers easily using the Import Wizard or importdata.

For example, consider the file grades.dat:

Class Grades for Spring Term
        Grade1 Grade2 Grade3
John     85      90     95
Ann      90      92     98
Martin  100      95     97
Rob      77      86     93

A call to importdata of the form

grades_imp = importdata('grades.dat');

Returns the same results as a call to the Import Wizard:

grades_imp = uiimport('grades.dat');

You can also start the Import Wizard by selecting File > Import Data.

Because the data includes both row and column headers, importdata or the Import Wizard returns the structure grades_imp as follows:

grades_imp = 
        data: [4x3 double]
    textdata: {6x1 cell}

grades_imp.data =
    85    90    95
    90    92    98
   100    95    97
    77    86    93

grades_imp.textdata = 
    'Class Grades for Spring Term'
    '        Grade1 Grade2 Grade3'
    'John'
    'Ann'
    'Martin'
    'Rob'

Additional Variables and Fields

If your data file includes either row headers or column headers, but not both:

Restrictions

If your file includes:

Back to Top

Importing Nonnumeric ASCII Data

To import an ASCII data file with fields that contain nonnumeric characters, use textscan.

For example, you can use textscan to import a file called mydata.dat:

Sally    09/12/2005 12.34 45 Yes
Larry    10/12/2005 34.56 54 Yes
Tommy    11/12/2005 67.89 23 No

Open the File

Preface any calls to textscan with a call to fopen to open the file for reading, and, when finished, close the file with fclose.

Describe Your Data

The textscan function is flexible, but requires that you specify more information about your file. Describe each field using format specifiers, such as '%s' for a string, '%d' for an integer, or '%f' for a floating-point number. (For a complete list of format specifiers, see the textscan reference page.)

Import into a Cell Array

Send textscan the file identifier and the format specifiers to describe the five fields in each row of mydata.dat. textscan returns a cell array with five cells:

fid = fopen('mydata.dat');
mydata = textscan(fid, '%s %s %f %d %s');
fclose(fid);

whos mydata
  Name        Size            Bytes  Class    Attributes

  mydata      1x5               952  cell 

mydata = 
  {3x1 cell}  {3x1 cell}  [3x1 double]  [3x1 int32]  {3x1 cell}

where

mydata{1} = {'Sally'; 'Larry'; 'Tommy'}
mydata{2} = {'09/12/2005'; '10/12/2005'; '11/12/2005'}
mydata{3} = [12.3400; 34.5600; 67.8900]
mydata{4} = [45; 54; 23]
mydata{5} = {'Yes'; 'Yes'; 'No'}

Back to Top

Importing Nonrectangular ASCII Data

Most of the ASCII data import functions require that your data is rectangular, that is, in a regular pattern of columns and rows. The textscan function relaxes this restriction, although it requires that your data is in a repeated pattern.

For example, you can use textscan to import a file called nonrect.dat:

begin
v1=12.67
v2=3.14
v3=6.778
end
begin
v1=21.78
v2=5.24
v3=9.838
end

Describe Your Data

To use textscan, describe the pattern of the data using format specifiers and delimiter parameters. Typical format specifiers include '%s' for a string, '%d' for an integer, or '%f' for a floating-point number. (For a complete list of format specifiers and parameters, see the textscan reference page.)

To import nonrect.dat, use the format specifier '%*s' to tell textscan to skip the strings 'begin' and 'end' . Include the literals 'v1=', 'v2=', and 'v3=' as part of the format specifiers, so that textscan ignores those strings as well.

Since each field is on a new line, the delimiter is a newline character ('\n'). To combine all the floating-point data into a single array, set the CollectOutput parameter to true. The final call to textscan is:

fid = fopen('nonrect.dat');

c = textscan(fid, ...            
                '%*s v1=%f v2=%f v3=%f %*s', ...
                'Delimiter', '\n', ...
                'CollectOutput', true);
  
fclose(fid);

whos c
Name      Size            Bytes  Class    Attributes

  c         1x1               108  cell               

c{1} =    
   12.6700    3.1400    6.7780
   21.7800    5.2400    9.8380

Back to Top

Importing Large ASCII Data Sets

To import large data files, consider using textscan to read the file in segments, which reduces the amount of memory required.

For example, suppose you want to process the file largefile.dat with the user-defined process_data function. This example assumes that the process_data function processes any number of lines of data, including zero.

clear segarray;
block_size = 10000;

% describe the format of the data
% for more information, see the textscan reference page
format = '%s %n %s %8.2f %8.2f %8.2f %8.2f %u8';

file_id = fopen('largefile.dat');

while ~feof(file_id)
   segarray = textscan(file_id, format, block_size);   
   process_data(segarray);
end

fclose(file_id);

The fopen function positions a pointer at the beginning of the file, and each read operation adjusts the location of that pointer. You can also use low-level file I/O functions such as fseek and frewind to reposition the pointer within the file. For more information, see Moving within a File.

Back to Top

Importing Text Data Files with Low-Level I/O

Low-level file I/O functions allow the most control over reading or writing data to a file. However, these functions require that you specify more detailed information about your file than the easier-to-use high-level functions, such as importdata. For more information on the high-level functions that read text files, see Importing Text Data Files.

If the high-level functions cannot import your data, use one of the following:

For additional information, see:

Reading Data in a Formatted Pattern

To import text files that importdata and textscan cannot read, consider using fscanf. The fscanf function requires that you describe the format of your file, but includes many options for this format description.

For example, create a text file mymeas.dat as shown. The data in mymeas.dat includes repeated sets of times, dates, and measurements. The header text includes the number of sets of measurements, N:

Measurement Data
N=3

12:00:00
01-Jan-1977
4.21  6.55  6.78  6.55
9.15  0.35  7.57  NaN
7.92  8.49  7.43  7.06
9.59  9.33  3.92  0.31
09:10:02
23-Aug-1990
2.76  6.94  4.38  1.86
0.46  3.17  NaN   4.89
0.97  9.50  7.65  4.45
8.23  0.34  7.95  6.46
15:03:40
15-Apr-2003
7.09  6.55  9.59  7.51
7.54  1.62  3.40  2.55
NaN   1.19  5.85  5.05
6.79  4.98  2.23  6.99

Opening the File.   As with any of the low-level I/O functions, before reading, open the file with fopen, and obtain a file identifier. By default, fopen opens files for read access, with a permission of 'r'.

When you finish processing the file, close it with fclose(fid).

Describing the Data.   Describe the data in the file with format specifiers, such as '%s' for a string, '%d' for an integer, or '%f' for a floating-point number. (For a complete list of specifiers, see the fscanf reference page.)

To skip literal characters in the file, include them in the format description. To skip a data field, use an asterisk ('*') in the specifier.

For example, consider the header lines of mymeas.dat:

Measurement Data   % skip 2 strings, go to next line:  %*s %*s\n
N=3                % ignore 'N=', read integer:  N=%d\n
                   % go to next line:  \n
12:00:00
01-Jan-1977
4.21  6.55  6.78  6.55
...

To read the headers and return the single value for N:

N = fscanf(fid, '%*s %*s\nN=%d\n\n', 1);

Specifying the Number of Values to Read.   By default, fscanf reapplies your format description until it cannot match the description to the data, or it reaches the end of the file.

Optionally, specify the number of values to read, so that fscanf does not attempt to read the entire file. For example, in mymeas.dat, each set of measurements includes a fixed number of rows and columns:

measrows = 4;
meascols = 4;
meas  = fscanf(fid, '%f', [measrows, meascols])';

Creating Variables in the Workspace.   There are several ways to store mymeas.dat in the MATLAB workspace. In this case, read the values into a structure. Each element of the structure has three fields: mtime, mdate, and meas.

filename = 'mymeas.dat';
measrows = 4;
meascols = 4;

% open the file
fid = fopen(filename);

% read the file headers, find N (one value)
N = fscanf(fid, '%*s %*s\nN=%d\n\n', 1);

% read each set of measurements
for n = 1:N
    mystruct(n).mtime = fscanf(fid, '%s', 1);
    mystruct(n).mdate = fscanf(fid, '%s', 1);

    % fscanf fills the array in column order,
    % so transpose the results
    mystruct(n).meas  = ...
      fscanf(fid, '%f', [measrows, meascols])';
end

% close the file
fclose(fid);

Reading Data Line-by-Line

MATLAB provides two functions that read lines from files and store them in string vectors: fgetl and fgets. The fgets function copies the newline character to the output string, but fgetl does not.

The following example uses fgetl to read an entire file one line at a time. The function litcount determines whether an input literal string (literal) appears in each line. If it does, the function prints the entire line preceded by the number of times the literal string appears on the line.

function y = litcount(filename, literal)
% Search for number of string matches per line.  

fid = fopen(filename);
y = 0;
tline = fgetl(fid);
while ischar(tline)
   matches = strfind(tline, literal);
   num = length(matches);
   if num > 0
      y = y + num;
      fprintf(1,'%d:%s\n',num,tline);
   end
   tline = fgetl(fid);
end
fclose(fid);

Create an input data file called badpoem:

Oranges and lemons,
Pineapples and tea.
Orangutans and monkeys,
Dragonflys or fleas.

To find out how many times the string 'an' appears in this file, call litcount:

litcount('badpoem','an')

This returns:

2: Oranges and lemons,
1: Pineapples and tea.
3: Orangutans and monkeys,
ans =
     6

Testing for End of File (EOF)

When you read a portion of your data at a time, you can use feof to check whether you have reached the end of the file. feof returns a value of 1 when the file pointer is at the end of the file. Otherwise, it returns 0.

Testing for EOF with feof.   When you use textscan, fscanf, or fread to read portions of data at a time, use feof to check whether you have reached the end of the file.

For example, suppose that the hypothetical file mymeas.dat has the following form, with no information about the number of measurement sets. Read the data into a structure with fields for mtime, mdate, and meas:

12:00:00
01-Jan-1977
4.21  6.55  6.78  6.55
9.15  0.35  7.57  NaN
7.92  8.49  7.43  7.06
9.59  9.33  3.92  0.31
09:10:02
23-Aug-1990
2.76  6.94  4.38  1.86
0.46  3.17  NaN   4.89
0.97  9.50  7.65  4.45
8.23  0.34  7.95  6.46

To read the file:

filename = 'mymeas.dat';
measrows = 4;
meascols = 4;

% open the file
fid = fopen(filename);

% make sure the file is not empty
finfo = dir(filename);
fsize = finfo.bytes;

if fsize > 0 

    % read the file
    block = 1;
    while ~feof(fid)
        mystruct(block).mtime = fscanf(fid, '%s', 1);
        mystruct(block).mdate = fscanf(fid, '%s', 1);

        % fscanf fills the array in column order,
        % so transpose the results
        mystruct(block).meas  = ...
          fscanf(fid, '%f', [measrows, meascols])';

        block = block + 1;
    end

end

% close the file
fclose(fid);

Testing for EOF with fgetl and fgets.   If you use fgetl or fgets in a control loop, feof is not always the best way to test for end of file. As an alternative, consider checking whether the value that fgetl or fgets returns is a character string.

For example, the function litcount described in Reading Data Line-by-Line includes the following while loop and fgetl calls :

y = 0;
tline = fgetl(fid);
while ischar(tline)
   matches = findstr(tline, literal);
   num = length(matches);
   if num > 0
      y = y + num;
      fprintf(1,'%d:%s\n',num,tline);
   end
   tline = fgetl(fid);
end

This approach is more robust than testing ~feof(fid) for two reasons:

Opening Files with Different Character Encodings

Encoding schemes support the characters required for particular alphabets, such as those for Japanese or European languages. Common encoding schemes include US-ASCII or UTF-8.

If you do not specify an encoding scheme, fopen opens files for processing using the default encoding for your system. To determine the default, open a file, and call fopen again with the syntax:

[filename, permission, machineformat, encoding] = fopen(fid);

If you specify an encoding scheme when you open a file, the following functions apply that scheme: fscanf, fprintf, fgetl, fgets, fread, and fwrite.

For a complete list of supported encoding schemes, and the syntax for specifying the encoding, see the fopen reference page.

Back to Top

  

Importing MAT-FilesImporting MAT-Files Importing XML DocumentsImporting XML Documents

Recommended Products

Get MATLAB trial software

Includes the most popular MATLAB recorded presentations with Q&A sessions led by MATLAB experts.

Get the Interactive Kit

 © 1984-2009- The MathWorks, Inc.    -   Site Help   -   Patents   -   Trademarks   -   Privacy Policy   -   Preventing Piracy   -   RSS