The liac-arff module implements functions to read and write ARFF files in Python. It was created in the Connectionist Artificial Intelligence Laboratory (LIAC), which takes place at the Federal University of Rio Grande do Sul (UFRGS), in Brazil.

ARFF (Attribute-Relation File Format) is an file format specially created for describe datasets which are used commonly for machine learning experiments and softwares. This file format was created to be used in Weka, the best representative software for machine learning automated experiments.

You can clone the arff-datasets repository for a large set of ARFF files.

• Read and write ARFF files using python built-in structures, such dictionaries and lists;
• Supports scipy.sparse.coo and lists of dictionaries as used by SVMLight
• Supports the following attribute types: NUMERIC, REAL, INTEGER, STRING, and NOMINAL;
• Has an interface similar to other built-in modules such as json, or zipfile;
• Supports read and write the descriptions of files;
• Supports missing values and names with spaces;
• Supports unicode values and names;
• Fully compatible with Python 3.6+;
• Under MIT License

Via pip:

$ pip install liac-arff

Via conda:

$ conda install -c conda-forge liac-arff

Manually:

$ pip install .

For a complete description of the module, consult the official documentation at http://packages.python.org/liac-arff/ with mirror in http://inf.ufrgs.br/~rppereira/docs/liac-arff/index.html

You can read an ARFF file as follows:

>>> import arff
>>> data = arff.load(open('wheater.arff', 'rb'))

Which results in:

>>> data
{
    u'attributes': [
        (u'outlook', [u'sunny', u'overcast', u'rainy']),
        (u'temperature', u'REAL'),
        (u'humidity', u'REAL'),
        (u'windy', [u'TRUE', u'FALSE']),
        (u'play', [u'yes', u'no'])],
    u'data': [
        [u'sunny', 85.0, 85.0, u'FALSE', u'no'],
        [u'sunny', 80.0, 90.0, u'TRUE', u'no'],
        [u'overcast', 83.0, 86.0, u'FALSE', u'yes'],
        [u'rainy', 70.0, 96.0, u'FALSE', u'yes'],
        [u'rainy', 68.0, 80.0, u'FALSE', u'yes'],
        [u'rainy', 65.0, 70.0, u'TRUE', u'no'],
        [u'overcast', 64.0, 65.0, u'TRUE', u'yes'],
        [u'sunny', 72.0, 95.0, u'FALSE', u'no'],
        [u'sunny', 69.0, 70.0, u'FALSE', u'yes'],
        [u'rainy', 75.0, 80.0, u'FALSE', u'yes'],
        [u'sunny', 75.0, 70.0, u'TRUE', u'yes'],
        [u'overcast', 72.0, 90.0, u'TRUE', u'yes'],
        [u'overcast', 81.0, 75.0, u'FALSE', u'yes'],
        [u'rainy', 71.0, 91.0, u'TRUE', u'no']
    ],
    u'description': u'',
    u'relation': u'weather'
}

You can write an ARFF file with this structure:

>>> print arff.dumps(data)
@RELATION weather

@ATTRIBUTE outlook {sunny, overcast, rainy}
@ATTRIBUTE temperature REAL
@ATTRIBUTE humidity REAL
@ATTRIBUTE windy {TRUE, FALSE}
@ATTRIBUTE play {yes, no}

@DATA
sunny,85.0,85.0,FALSE,no
sunny,80.0,90.0,TRUE,no
overcast,83.0,86.0,FALSE,yes
rainy,70.0,96.0,FALSE,yes
rainy,68.0,80.0,FALSE,yes
rainy,65.0,70.0,TRUE,no
overcast,64.0,65.0,TRUE,yes
sunny,72.0,95.0,FALSE,no
sunny,69.0,70.0,FALSE,yes
rainy,75.0,80.0,FALSE,yes
sunny,75.0,70.0,TRUE,yes
overcast,72.0,90.0,TRUE,yes
overcast,81.0,75.0,FALSE,yes
rainy,71.0,91.0,TRUE,no
%
%
%

• Nate Moseley (FinalDoom)
• Tarek Amr (gr33ndata)
• Simon (M3t0r)
• Gonzalo Almeida (flecox)
• André Nordbø (AndyNor)
• Niedakh
• Zichen Wang (wangz10)
• Matthias Feurer (mfeurer)
• Hongjoo Lee (midnightradio)
• Calvin Jeong (calvin)
• Joel Nothman (jnothman)
• Guillaume Lemaitre (glemaitre)
• Roman Yurchak (rth)
• Karthikeyan Singaravelan (tirkarthi)

https://github.com/renatopp/liac-arff