76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
"""US Capital Punishment dataset."""
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from statsmodels.datasets import utils as du
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__docformat__ = 'restructuredtext'
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COPYRIGHT = """Used with express permission from the original author,
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who retains all rights."""
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TITLE = __doc__
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SOURCE = """
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Jeff Gill's `Generalized Linear Models: A Unified Approach`
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http://jgill.wustl.edu/research/books.html
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"""
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DESCRSHORT = """Number of state executions in 1997"""
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DESCRLONG = """This data describes the number of times capital punishment is implemented
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at the state level for the year 1997. The outcome variable is the number of
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executions. There were executions in 17 states.
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Included in the data are explanatory variables for median per capita income
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in dollars, the percent of the population classified as living in poverty,
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the percent of Black citizens in the population, the rate of violent
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crimes per 100,000 residents for 1996, a dummy variable indicating
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whether the state is in the South, and (an estimate of) the proportion
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of the population with a college degree of some kind.
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"""
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NOTE = """::
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Number of Observations - 17
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Number of Variables - 7
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Variable name definitions::
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EXECUTIONS - Executions in 1996
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INCOME - Median per capita income in 1996 dollars
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PERPOVERTY - Percent of the population classified as living in poverty
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PERBLACK - Percent of black citizens in the population
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VC100k96 - Rate of violent crimes per 100,00 residents for 1996
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SOUTH - SOUTH == 1 indicates a state in the South
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DEGREE - An esimate of the proportion of the state population with a
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college degree of some kind
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State names are included in the data file, though not returned by load.
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"""
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def load_pandas():
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"""
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Load the cpunish data and return a Dataset class.
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Returns
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-------
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Dataset
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See DATASET_PROPOSAL.txt for more information.
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"""
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data = _get_data()
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return du.process_pandas(data, endog_idx=0)
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def load():
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"""
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Load the cpunish data and return a Dataset class.
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Returns
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-------
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Dataset
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See DATASET_PROPOSAL.txt for more information.
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"""
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return load_pandas()
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def _get_data():
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data = du.load_csv(__file__, 'cpunish.csv')
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data = data.iloc[:, 1:8].astype(float)
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return data
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