"""Longley dataset"""

__docformat__ = 'restructuredtext'

COPYRIGHT   = """This is public domain."""
TITLE       = __doc__
SOURCE      = """
The classic 1967 Longley Data

http://www.itl.nist.gov/div898/strd/lls/data/Longley.shtml

::

    Longley, J.W. (1967) "An Appraisal of Least Squares Programs for the
        Electronic Comptuer from the Point of View of the User."  Journal of
        the American Statistical Association.  62.319, 819-41.
"""

DESCRSHORT  = """"""

DESCRLONG   = """The Longley dataset contains various US macroeconomic
variables that are known to be highly collinear.  It has been used to appraise
the accuracy of least squares routines."""

NOTE        = """::

    Number of Observations - 16

    Number of Variables - 6

    Variable name definitions::

            TOTEMP - Total Employment
            GNPDEFL - GNP deflator
            GNP - GNP
            UNEMP - Number of unemployed
            ARMED - Size of armed forces
            POP - Population
            YEAR - Year (1947 - 1962)
"""

from numpy import recfromtxt, array, column_stack
from statsmodels.datasets import utils as du
from os.path import dirname, abspath

def load():
    """
    Load the Longley data and return a Dataset class.

    Returns
    -------
    Dataset instance
        See DATASET_PROPOSAL.txt for more information.
    """
    data = _get_data()
    return du.process_recarray(data, endog_idx=0, dtype=float)

def load_pandas():
    """
    Load the Longley data and return a Dataset class.

    Returns
    -------
    Dataset instance
        See DATASET_PROPOSAL.txt for more information.
    """
    data = _get_data()
    return du.process_recarray_pandas(data, endog_idx=0)

def _get_data():
    filepath = dirname(abspath(__file__))
    with open(filepath+'/longley.csv',"rb") as f:
        data = recfromtxt(f, delimiter=",",
                          names=True, dtype=float, usecols=(1,2,3,4,5,6,7))
    return data