prepare-basic.py

import pandas as pd
import numpy as np

from util import Dataset

for name in ['train', 'test']:
    print "Processing %s..." % name
    data = pd.read_csv('../input/%s.csv.zip' % name)

    # Save column names
    if name == 'train':
        cat_columns = [c for c in data.columns if c.startswith('cat')]
        num_columns = [c for c in data.columns if c.startswith('cont')]

        Dataset.save_part_features('categorical', cat_columns)
        Dataset.save_part_features('numeric', num_columns)

    Dataset(categorical=data[cat_columns].values).save(name)
    Dataset(numeric=data[num_columns].values.astype(np.float32)).save(name)
    Dataset(id=data['id']).save(name)

    if 'loss' in data.columns:
        Dataset(loss=data['loss']).save(name)


print "Done."