def make_full():
sfc.msg('Make full dataset')
train = sfc.get_data('data/train.csv')
# Formatting
formatter = sfc.DataFormat()
train = formatter.add_columns_enumerate(train)
train = formatter.add_columns_time(train)
train = formatter.add_weather(train)
make_dataset(train, 'data/all.csv',
comment='All training data')
return
def make_test():
sfc.msg('Make test dataset')
test = sfc.get_data('data/test.csv')
# Formatting
formatter = sfc.DataFormat()
test = formatter.add_columns_enumerate(test)
test = formatter.add_columns_time(test)
test = formatter.add_weather(test)
make_dataset(test, 'data/test_format.csv',
comment='Formatted test data')
test = test.sort('Id', ascending=True).reset_index(drop=True)
return test
def make_trimmed():
sfc.msg('Make trimmed datasets')
train = sfc.get_data('data/train.csv')
trimmed = trim_categories(train)
# Formatting
formatter = sfc.DataFormat()
trimmed = formatter.add_columns_enumerate(trimmed)
trimmed = formatter.add_columns_time(trimmed)
trimmed = formatter.add_weather(trimmed)
# Make the actual datasets
make_dataset(trimmed, 'data/trim_1e4.csv', size=10000,
comment='Random set of training data. ' \
'Selected Categories, 1e4 records')
#make_dataset(trimmed, 'data/trim_1e5.csv', size=100000,
#comment='Random set of training data. ' \
#'Selected Categories, 1e5 records')
#make_dataset(trimmed, 'data/trim.csv',
#comment='Random set of training data. ' \
#'Selected Categories, all records')
return
def make_dataset(input, output, comment='', size=None):
sfc.msg('making {}'.format(output))
data = None
# Get the input data
if isinstance(input, str):
if not os.path.exists(input):
input2 = os.path.join('data', input)
if not os.path.exists(input2):
raise IOError('Neither {} nor {} exist'.format(input, input2))
input = input2
data = sfc.get_data(input)
elif isinstance(input, pandas.DataFrame):
data = copy.deepcopy(input)
else:
raise IOError('Cannot deal with a {}'.format(type(input)))
# Shrink to random records
if size is not None and size < len(data):
random.seed(sfc._SEED)
data = data.ix[sorted(random.sample(xrange(len(data)), size))]
data.reset_index(drop=True)
sfc.write_data(data, output, comment=comment)
return
# Formatting
formatter = sfc.DataFormat()
train = formatter.add_columns_enumerate(train)
train = formatter.add_columns_time(train)
train = formatter.add_weather(train)
make_dataset(train, 'data/all.csv',
comment='All training data')
return
def make_test():
sfc.msg('Make test dataset')
test = sfc.get_data('data/test.csv')
# Formatting
formatter = sfc.DataFormat()
test = formatter.add_columns_enumerate(test)
test = formatter.add_columns_time(test)
test = formatter.add_weather(test)
make_dataset(test, 'data/test_format.csv',
comment='Formatted test data')
test = test.sort('Id', ascending=True).reset_index(drop=True)
return test
if __name__ == "__main__":
sfc.msg(1)
make_trimmed()
#make_full()
make_test()
###############################################################################
