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: 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 width's type is numeric height's type is numeric color's type is nominal, range is ('red', 'green', 'blue', 'yellow', 'black')