code: def loadarff(f):
      """
      Read an arff file.
  
      The data is returned as a record array, which can be accessed much like
      a dictionary of NumPy arrays. For example, if one of the attributes is
      called 'pressure', then its first 10 data points can be accessed from the
      ``data`` record array like so: ``data['pressure'][0:10]``
  
  
      Parameters
      ----------
      f : file-like or str
         File-like object to read from, or filename to open.
  
      Returns
      -------
      data : record array
         The data of the arff file, accessible by attribute names.
      meta : `MetaData`
         Contains information about the arff file such as name and
         type of attributes, the relation (name of the dataset), etc.
  
      Raises
      ------
      ParseArffError
          This is raised if the given file is not ARFF-formatted.
      NotImplementedError
          The ARFF file has an attribute which is not supported yet.
  
      Notes
      -----
  
      This function should be able to read most arff files. Not
      implemented functionality include:
  
      * date type attributes
      * string type attributes
  
      It can read files with numeric and nominal attributes. It cannot read
      files with sparse data ({} in the file). However, this function can
      read files with missing data (? in the file), representing the data
      points as NaNs.
  
      Examples
      --------
      >>> from scipy.io import arff
      >>> from io import StringIO
      >>> content = \"\"\"
      ... @relation foo
      ... @attribute width  numeric
      ... @attribute height numeric
      ... @attribute color  {red,green,blue,yellow,black}
      ... @data
      ... 5.0,3.25,blue
      ... 4.5,3.75,green
      ... 3.0,4.00,red
      ... \"\"\"
      >>> f = StringIO(content)
      >>> data, meta = arff.loadarff(f)
      >>> data
      array([(5.0, 3.25, 'blue'), (4.5, 3.75, 'green'), (3.0, 4.0, 'red')],
            dtype=[('width', '<f8'), ('height', '<f8'), ('color', '|S6')])
      >>> meta
      Dataset: foo
      \twidth's type is numeric
      \theight's type is numeric
      \tcolor's type is nominal, range is ('red', 'green', 'blue', 'yellow', 'black')
  
      """
      if hasattr(f, "read"):
          ofile = f
      else:
          ofile = open(f)
      try:
          return _loadarff(ofile)
      finally:
          if ofile is not f:  # only close what we opened
              ofile.close()
  
imports: import re
  import datetime
  import numpy
  import csv
  import ctypes
label_desc: Use image node_id 10 for calling a global function with example usage: loadarff(f) and returns: _loadarff