"""American National Election Survey 1996""" from numpy import log from statsmodels.datasets import utils as du __docformat__ = 'restructuredtext' COPYRIGHT = """This is public domain.""" TITLE = __doc__ SOURCE = """ http://www.electionstudies.org/ The American National Election Studies. """ DESCRSHORT = """This data is a subset of the American National Election Studies of 1996.""" DESCRLONG = DESCRSHORT NOTE = """:: Number of observations - 944 Number of variables - 10 Variables name definitions:: popul - Census place population in 1000s TVnews - Number of times per week that respondent watches TV news. PID - Party identification of respondent. 0 - Strong Democrat 1 - Weak Democrat 2 - Independent-Democrat 3 - Independent-Indpendent 4 - Independent-Republican 5 - Weak Republican 6 - Strong Republican age : Age of respondent. educ - Education level of respondent 1 - 1-8 grades 2 - Some high school 3 - High school graduate 4 - Some college 5 - College degree 6 - Master's degree 7 - PhD income - Income of household 1 - None or less than $2,999 2 - $3,000-$4,999 3 - $5,000-$6,999 4 - $7,000-$8,999 5 - $9,000-$9,999 6 - $10,000-$10,999 7 - $11,000-$11,999 8 - $12,000-$12,999 9 - $13,000-$13,999 10 - $14,000-$14.999 11 - $15,000-$16,999 12 - $17,000-$19,999 13 - $20,000-$21,999 14 - $22,000-$24,999 15 - $25,000-$29,999 16 - $30,000-$34,999 17 - $35,000-$39,999 18 - $40,000-$44,999 19 - $45,000-$49,999 20 - $50,000-$59,999 21 - $60,000-$74,999 22 - $75,000-89,999 23 - $90,000-$104,999 24 - $105,000 and over vote - Expected vote 0 - Clinton 1 - Dole The following 3 variables all take the values: 1 - Extremely liberal 2 - Liberal 3 - Slightly liberal 4 - Moderate 5 - Slightly conservative 6 - Conservative 7 - Extremely Conservative selfLR - Respondent's self-reported political leanings from "Left" to "Right". ClinLR - Respondents impression of Bill Clinton's political leanings from "Left" to "Right". DoleLR - Respondents impression of Bob Dole's political leanings from "Left" to "Right". logpopul - log(popul + .1) """ def load_pandas(): """Load the anes96 data and returns a Dataset class. Returns ------- Dataset See DATASET_PROPOSAL.txt for more information. """ data = _get_data() return du.process_pandas(data, endog_idx=5, exog_idx=[10, 2, 6, 7, 8]) def load(): """Load the anes96 data and returns a Dataset class. Returns ------- Dataset See DATASET_PROPOSAL.txt for more information. """ return load_pandas() def _get_data(): data = du.load_csv(__file__, 'anes96.csv', sep=r'\s') data = du.strip_column_names(data) data['logpopul'] = log(data['popul'] + .1) return data.astype(float)