scipy.io.arff.loadarff#

scipy.io.arff.loadarff(f)[source]#

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

ffile-like or str: File-like object to read from, or filename to open.

Returns

datarecord array: The data of the arff file, accessible by attribute names.
metaMetaData: 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
    width's type is numeric
    height's type is numeric
    color's type is nominal, range is ('red', 'green', 'blue', 'yellow', 'black')

scipy.io.wavfile.WavFileWarning

scipy.io.arff.MetaData