"""Stack loss data"""
__docformat__ = 'restructuredtext'
COPYRIGHT = """This is public domain. """
TITLE = __doc__
SOURCE = """
Brownlee, K. A. (1965), "Statistical Theory and Methodology in
Science and Engineering", 2nd edition, New York:Wiley.
"""
DESCRSHORT = """Stack loss plant data of Brownlee (1965)"""
DESCRLONG = """The stack loss plant data of Brownlee (1965) contains
21 days of measurements from a plant's oxidation of ammonia to nitric acid.
The nitric oxide pollutants are captured in an absorption tower."""
NOTE = """::
Number of Observations - 21
Number of Variables - 4
Variable name definitions::
STACKLOSS - 10 times the percentage of ammonia going into the plant
that escapes from the absoroption column
AIRFLOW - Rate of operation of the plant
WATERTEMP - Cooling water temperature in the absorption tower
ACIDCONC - Acid concentration of circulating acid minus 50 times 10.
"""
from numpy import recfromtxt, column_stack, array
from statsmodels.datasets import utils as du
from os.path import dirname, abspath
[docs]def load():
"""
Load the stack loss data and returns a Dataset class instance.
Returns
--------
Dataset instance:
See DATASET_PROPOSAL.txt for more information.
"""
data = _get_data()
return du.process_recarray(data, endog_idx=0, dtype=float)
[docs]def load_pandas():
"""
Load the stack loss data and returns a Dataset class instance.
Returns
--------
Dataset instance:
See DATASET_PROPOSAL.txt for more information.
"""
data = _get_data()
return du.process_recarray_pandas(data, endog_idx=0, dtype=float)
def _get_data():
filepath = dirname(abspath(__file__))
data = recfromtxt(open(filepath + '/stackloss.csv',"rb"), delimiter=",",
names=True, dtype=float)
return data