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2025-07-30 17:09:11 +03:00
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.venv/lib/python3.12/site-packages/statsmodels/datasets/fair/__init__.py Normal file
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__all__ = ["load", "load_pandas",
"COPYRIGHT", "TITLE", "SOURCE", "DESCRSHORT", "DESCRLONG", "NOTE"]
from .data import (
load, load_pandas,
COPYRIGHT, TITLE, SOURCE, DESCRSHORT, DESCRLONG, NOTE)

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"""Fair's Extramarital Affairs Data"""
from statsmodels.datasets import utils as du
__docformat__ = 'restructuredtext'
COPYRIGHT = """Included with permission of the author."""
TITLE = """Affairs dataset"""
SOURCE = """
Fair, Ray. 1978. "A Theory of Extramarital Affairs," `Journal of Political
Economy`, February, 45-61.
The data is available at http://fairmodel.econ.yale.edu/rayfair/pdf/2011b.htm
"""
DESCRSHORT = """Extramarital affair data."""
DESCRLONG = """Extramarital affair data used to explain the allocation
of an individual's time among work, time spent with a spouse, and time
spent with a paramour. The data is used as an example of regression
with censored data."""
#suggested notes
NOTE = """::
Number of observations: 6366
Number of variables: 9
Variable name definitions:
rate_marriage : How rate marriage, 1 = very poor, 2 = poor, 3 = fair,
4 = good, 5 = very good
age : Age
yrs_married : No. years married. Interval approximations. See
original paper for detailed explanation.
children : No. children
religious : How relgious, 1 = not, 2 = mildly, 3 = fairly,
4 = strongly
educ : Level of education, 9 = grade school, 12 = high
school, 14 = some college, 16 = college graduate,
17 = some graduate school, 20 = advanced degree
occupation : 1 = student, 2 = farming, agriculture; semi-skilled,
or unskilled worker; 3 = white-colloar; 4 = teacher
counselor social worker, nurse; artist, writers;
technician, skilled worker, 5 = managerial,
administrative, business, 6 = professional with
advanced degree
occupation_husb : Husband's occupation. Same as occupation.
affairs : measure of time spent in extramarital affairs
See the original paper for more details.
"""
def load():
"""
Load the data and return a Dataset class instance.
Returns
-------
Dataset
See DATASET_PROPOSAL.txt for more information.
"""
return load_pandas()
def load_pandas():
data = _get_data()
return du.process_pandas(data, endog_idx=8, exog_idx=None)
def _get_data():
return du.load_csv(__file__, 'fair.csv', convert_float=True)

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identifier,constant,sex,age,nmarried,nchildren,religious,education,occupation,rate_marriage,naffairs
4,1.0,1,37.0,10.0,0,3,18.0,7,4,0.0
5,1.0,0,27.0,4.0,0,4,14.0,6,4,0.0
11,1.0,0,32.0,15.0,1,1,12.0,1,4,0.0
16,1.0,1,57.0,15.0,1,5,18.0,6,5,0.0
23,1.0,1,22.0,0.75,0,2,17.0,6,3,0.0
29,1.0,0,32.0,1.5,0,2,17.0,5,5,0.0
44,1.0,0,22.0,0.75,0,2,12.0,1,3,0.0
45,1.0,1,57.0,15.0,1,2,14.0,4,4,0.0
47,1.0,0,32.0,15.0,1,4,16.0,1,2,0.0
49,1.0,1,22.0,1.5,0,4,14.0,4,5,0.0
50,1.0,1,37.0,15.0,1,2,20.0,7,2,0.0
55,1.0,1,27.0,4.0,1,4,18.0,6,4,0.0
64,1.0,1,47.0,15.0,1,5,17.0,6,4,0.0
80,1.0,0,22.0,1.5,0,2,17.0,5,4,0.0
86,1.0,0,27.0,4.0,0,4,14.0,5,4,0.0
93,1.0,0,37.0,15.0,1,1,17.0,5,5,0.0
108,1.0,0,37.0,15.0,1,2,18.0,4,3,0.0
114,1.0,0,22.0,0.75,0,3,16.0,5,4,0.0
115,1.0,0,22.0,1.5,0,2,16.0,5,5,0.0
116,1.0,0,27.0,10.0,1,2,14.0,1,5,0.0
123,1.0,0,22.0,1.5,0,2,16.0,5,5,0.0
127,1.0,0,22.0,1.5,0,2,16.0,5,5,0.0
129,1.0,0,27.0,10.0,1,4,16.0,5,4,0.0
134,1.0,0,32.0,10.0,1,3,14.0,1,5,0.0
137,1.0,1,37.0,4.0,1,2,20.0,6,4,0.0
139,1.0,0,22.0,1.5,0,2,18.0,5,5,0.0
147,1.0,0,27.0,7.0,0,4,16.0,1,5,0.0
151,1.0,1,42.0,15.0,1,5,20.0,6,4,0.0
153,1.0,1,27.0,4.0,1,3,16.0,5,5,0.0
155,1.0,0,27.0,4.0,1,3,17.0,5,4,0.0
162,1.0,1,42.0,15.0,1,4,20.0,6,3,0.0
163,1.0,0,22.0,1.5,0,3,16.0,5,5,0.0
165,1.0,1,27.0,0.417,0,4,17.0,6,4,0.0
168,1.0,0,42.0,15.0,1,5,14.0,5,4,0.0
170,1.0,1,32.0,4.0,1,1,18.0,6,4,0.0
172,1.0,0,22.0,1.5,0,4,16.0,5,3,0.0
184,1.0,0,42.0,15.0,1,3,12.0,1,4,0.0
187,1.0,0,22.0,4.0,0,4,17.0,5,5,0.0
192,1.0,1,22.0,1.5,1,1,14.0,3,5,0.0
194,1.0,0,22.0,0.75,0,3,16.0,1,5,0.0
210,1.0,1,32.0,10.0,1,5,20.0,6,5,0.0
217,1.0,1,52.0,15.0,1,5,18.0,6,3,0.0
220,1.0,0,22.0,0.417,0,5,14.0,1,4,0.0
224,1.0,0,27.0,4.0,1,2,18.0,6,1,0.0
227,1.0,0,32.0,7.0,1,5,17.0,5,3,0.0
228,1.0,1,22.0,4.0,0,3,16.0,5,5,0.0
239,1.0,0,27.0,7.0,1,4,18.0,6,5,0.0
241,1.0,0,42.0,15.0,1,2,18.0,5,4,0.0
245,1.0,1,27.0,1.5,1,4,16.0,3,5,0.0
249,1.0,1,42.0,15.0,1,2,20.0,6,4,0.0
262,1.0,0,22.0,0.75,0,5,14.0,3,5,0.0
265,1.0,1,32.0,7.0,1,2,20.0,6,4,0.0
267,1.0,1,27.0,4.0,1,5,20.0,6,5,0.0
269,1.0,1,27.0,10.0,1,4,20.0,6,4,0.0
271,1.0,1,22.0,4.0,0,1,18.0,5,5,0.0
277,1.0,0,37.0,15.0,1,4,14.0,3,1,0.0
290,1.0,1,22.0,1.5,1,5,16.0,4,4,0.0
292,1.0,0,37.0,15.0,1,4,17.0,1,5,0.0
293,1.0,0,27.0,0.75,0,4,17.0,5,4,0.0
295,1.0,1,32.0,10.0,1,4,20.0,6,4,0.0
299,1.0,0,47.0,15.0,1,5,14.0,7,2,0.0
320,1.0,1,37.0,10.0,1,3,20.0,6,4,0.0
321,1.0,0,22.0,0.75,0,2,16.0,5,5,0.0
324,1.0,1,27.0,4.0,0,2,18.0,4,5,0.0
334,1.0,1,32.0,7.0,0,4,20.0,6,4,0.0
351,1.0,1,42.0,15.0,1,2,17.0,3,5,0.0
355,1.0,1,37.0,10.0,1,4,20.0,6,4,0.0
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362,1.0,0,22.0,1.5,0,5,16.0,5,5,0.0
366,1.0,0,27.0,1.5,0,2,16.0,6,4,0.0
370,1.0,0,27.0,4.0,0,3,17.0,5,5,0.0
374,1.0,0,32.0,10.0,1,5,14.0,4,5,0.0
378,1.0,0,22.0,0.125,0,2,12.0,5,5,0.0
381,1.0,1,47.0,15.0,1,4,14.0,4,3,0.0
382,1.0,1,32.0,15.0,1,1,14.0,5,5,0.0
383,1.0,1,27.0,7.0,1,4,16.0,5,5,0.0
384,1.0,0,22.0,1.5,1,3,16.0,5,5,0.0
400,1.0,1,27.0,4.0,1,3,17.0,6,5,0.0
403,1.0,0,22.0,1.5,0,3,16.0,5,5,0.0
409,1.0,1,57.0,15.0,1,2,14.0,7,2,0.0
412,1.0,1,17.5,1.5,1,3,18.0,6,5,0.0
413,1.0,1,57.0,15.0,1,4,20.0,6,5,0.0
416,1.0,0,22.0,0.75,0,2,16.0,3,4,0.0
418,1.0,1,42.0,4.0,0,4,17.0,3,3,0.0
422,1.0,0,22.0,1.5,1,4,12.0,1,5,0.0
435,1.0,0,22.0,0.417,0,1,17.0,6,4,0.0
439,1.0,0,32.0,15.0,1,4,17.0,5,5,0.0
445,1.0,0,27.0,1.5,0,3,18.0,5,2,0.0
447,1.0,0,22.0,1.5,1,3,14.0,1,5,0.0
448,1.0,0,37.0,15.0,1,3,14.0,1,4,0.0
449,1.0,0,32.0,15.0,1,4,14.0,3,4,0.0
478,1.0,1,37.0,10.0,1,2,14.0,5,3,0.0
482,1.0,1,37.0,10.0,1,4,16.0,5,4,0.0
486,1.0,1,57.0,15.0,1,5,20.0,5,3,0.0
489,1.0,1,27.0,0.417,0,1,16.0,3,4,0.0
490,1.0,0,42.0,15.0,1,5,14.0,1,5,0.0
491,1.0,1,57.0,15.0,1,3,16.0,6,1,0.0
492,1.0,1,37.0,10.0,1,1,16.0,6,4,0.0
503,1.0,1,37.0,15.0,1,3,17.0,5,5,0.0
508,1.0,1,37.0,15.0,1,4,20.0,6,5,0.0
509,1.0,0,27.0,10.0,1,5,14.0,1,5,0.0
512,1.0,1,37.0,10.0,1,2,18.0,6,4,0.0
515,1.0,0,22.0,0.125,0,4,12.0,4,5,0.0
517,1.0,1,57.0,15.0,1,5,20.0,6,5,0.0
532,1.0,0,37.0,15.0,1,4,18.0,6,4,0.0
533,1.0,1,22.0,4.0,1,4,14.0,6,4,0.0
535,1.0,1,27.0,7.0,1,4,18.0,5,4,0.0
537,1.0,1,57.0,15.0,1,4,20.0,5,4,0.0
538,1.0,1,32.0,15.0,1,3,14.0,6,3,0.0
543,1.0,0,22.0,1.5,0,2,14.0,5,4,0.0
547,1.0,0,32.0,7.0,1,4,17.0,1,5,0.0
550,1.0,0,37.0,15.0,1,4,17.0,6,5,0.0
558,1.0,0,32.0,1.5,0,5,18.0,5,5,0.0
571,1.0,1,42.0,10.0,1,5,20.0,7,4,0.0
578,1.0,0,27.0,7.0,0,3,16.0,5,4,0.0
583,1.0,1,37.0,15.0,0,4,20.0,6,5,0.0
586,1.0,1,37.0,15.0,1,4,14.0,3,2,0.0
594,1.0,1,32.0,10.0,0,5,18.0,6,4,0.0
597,1.0,0,22.0,0.75,0,4,16.0,1,5,0.0
602,1.0,0,27.0,7.0,1,4,12.0,2,4,0.0
603,1.0,0,27.0,7.0,1,2,16.0,2,5,0.0
604,1.0,0,42.0,15.0,1,5,18.0,5,4,0.0
612,1.0,1,42.0,15.0,1,4,17.0,5,3,0.0
613,1.0,0,27.0,7.0,1,2,16.0,1,2,0.0
621,1.0,0,22.0,1.5,0,3,16.0,5,5,0.0
627,1.0,1,37.0,15.0,1,5,20.0,6,5,0.0
630,1.0,0,22.0,0.125,0,2,14.0,4,5,0.0
631,1.0,1,27.0,1.5,0,4,16.0,5,5,0.0
632,1.0,1,32.0,1.5,0,2,18.0,6,5,0.0
639,1.0,1,27.0,1.5,0,2,17.0,6,5,0.0
645,1.0,0,27.0,10.0,1,4,16.0,1,3,0.0
647,1.0,1,42.0,15.0,1,4,18.0,6,5,0.0
648,1.0,0,27.0,1.5,0,2,16.0,6,5,0.0
651,1.0,1,27.0,4.0,0,2,18.0,6,3,0.0
655,1.0,0,32.0,10.0,1,3,14.0,5,3,0.0
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670,1.0,0,22.0,0.75,0,2,18.0,6,5,0.0
671,1.0,0,37.0,15.0,1,2,16.0,1,4,0.0
673,1.0,1,27.0,4.0,1,4,20.0,5,5,0.0
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706,1.0,0,32.0,15.0,1,5,18.0,6,4,0.0
709,1.0,1,27.0,7.0,1,5,12.0,5,3,0.0
717,1.0,1,52.0,15.0,1,2,18.0,5,4,0.0
719,1.0,1,27.0,4.0,0,3,20.0,6,3,0.0
723,1.0,1,37.0,4.0,1,1,18.0,5,4,0.0
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737,1.0,1,22.0,0.75,0,2,14.0,4,3,0.0
739,1.0,1,32.0,4.0,1,2,18.0,5,3,0.0
743,1.0,1,37.0,15.0,1,4,20.0,6,3,0.0
745,1.0,1,22.0,0.75,1,2,14.0,4,3,0.0
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751,1.0,0,52.0,15.0,1,5,17.0,1,1,0.0
752,1.0,0,37.0,15.0,1,4,14.0,1,2,0.0
754,1.0,1,27.0,7.0,1,4,14.0,5,3,0.0
760,1.0,1,32.0,4.0,1,2,16.0,5,5,0.0
763,1.0,0,27.0,4.0,1,2,18.0,6,5,0.0
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794,1.0,0,57.0,15.0,1,2,18.0,5,2,0.0
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798,1.0,1,42.0,15.0,1,3,14.0,3,4,0.0
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803,1.0,1,57.0,15.0,1,4,20.0,6,5,0.0
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830,1.0,1,32.0,0.125,1,2,18.0,5,2,0.0
843,1.0,0,27.0,4.0,0,3,16.0,5,4,0.0
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851,1.0,0,32.0,7.0,1,4,16.0,1,3,0.0
854,1.0,0,37.0,15.0,1,4,14.0,5,4,0.0
856,1.0,0,42.0,15.0,1,5,17.0,6,2,0.0
857,1.0,1,32.0,1.5,1,4,14.0,6,5,0.0
859,1.0,0,32.0,4.0,1,3,17.0,5,3,0.0
863,1.0,0,37.0,7.0,0,4,18.0,5,5,0.0
865,1.0,0,22.0,0.417,1,3,14.0,3,5,0.0
867,1.0,0,27.0,7.0,1,4,14.0,1,5,0.0
870,1.0,1,27.0,0.75,0,3,16.0,5,5,0.0
873,1.0,1,27.0,4.0,1,2,20.0,5,5,0.0
875,1.0,1,32.0,10.0,1,4,16.0,4,5,0.0
876,1.0,1,32.0,15.0,1,1,14.0,5,5,0.0
877,1.0,1,22.0,0.75,0,3,17.0,4,5,0.0
880,1.0,0,27.0,7.0,1,4,17.0,1,4,0.0
903,1.0,1,27.0,0.417,1,4,20.0,5,4,0.0
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920,1.0,0,22.0,1.5,0,3,16.0,6,5,0.0
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931,1.0,0,22.0,1.5,0,1,14.0,1,5,0.0
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1423,1.0,1,27.0,4.0,1,3,16.0,4,5,0.0
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1617,1.0,0,47.0,15.0,1,3,16.0,5,4,0.0
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1621,1.0,0,22.0,1.5,1,2,14.0,5,5,0.0
1637,1.0,0,27.0,4.0,1,1,16.0,5,5,0.0
1638,1.0,1,52.0,15.0,1,4,16.0,5,5,0.0
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1654,1.0,1,47.0,15.0,1,4,16.0,6,4,0.0
1665,1.0,0,27.0,7.0,1,2,14.0,1,2,0.0
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1671,1.0,0,32.0,10.0,1,2,16.0,5,4,0.0
1675,1.0,0,22.0,0.75,0,2,16.0,5,4,0.0
1688,1.0,0,22.0,1.5,0,2,16.0,5,5,0.0
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1752,1.0,1,22.0,1.5,0,2,18.0,5,3,0.0
1754,1.0,1,27.0,4.0,1,5,17.0,2,5,0.0
1758,1.0,0,27.0,4.0,1,4,12.0,1,5,0.0
1761,1.0,1,42.0,15.0,1,5,18.0,5,4,0.0
1773,1.0,1,32.0,1.5,0,2,20.0,7,3,0.0
1775,1.0,1,57.0,15.0,0,4,9.0,3,1,0.0
1786,1.0,1,37.0,7.0,0,4,18.0,5,5,0.0
1793,1.0,1,52.0,15.0,1,2,17.0,5,4,0.0
1799,1.0,1,47.0,15.0,1,4,17.0,6,5,0.0
1803,1.0,0,27.0,7.0,0,2,17.0,5,4,0.0
1806,1.0,0,27.0,7.0,1,4,14.0,5,5,0.0
1807,1.0,0,22.0,4.0,0,2,14.0,3,3,0.0
1808,1.0,1,37.0,7.0,1,2,20.0,6,5,0.0
1814,1.0,1,27.0,7.0,0,4,12.0,4,3,0.0
1815,1.0,1,42.0,10.0,1,4,18.0,6,4,0.0
1818,1.0,0,22.0,1.5,0,3,14.0,1,5,0.0
1827,1.0,0,22.0,4.0,1,2,14.0,1,3,0.0
1834,1.0,0,57.0,15.0,0,4,20.0,6,5,0.0
1835,1.0,1,37.0,15.0,1,4,14.0,4,3,0.0
1843,1.0,0,27.0,7.0,1,3,18.0,5,5,0.0
1846,1.0,0,17.5,10.0,0,4,14.0,4,5,0.0
1850,1.0,1,22.0,4.0,1,4,16.0,5,5,0.0
1851,1.0,0,27.0,4.0,1,2,16.0,1,4,0.0
1854,1.0,0,37.0,15.0,1,2,14.0,5,1,0.0
1859,1.0,0,22.0,1.5,0,5,14.0,1,4,0.0
1861,1.0,1,27.0,7.0,1,2,20.0,5,4,0.0
1866,1.0,1,27.0,4.0,1,4,14.0,5,5,0.0
1873,1.0,1,22.0,0.125,0,1,16.0,3,5,0.0
1875,1.0,0,27.0,7.0,1,4,14.0,1,4,0.0
1885,1.0,0,32.0,15.0,1,5,16.0,5,3,0.0
1892,1.0,1,32.0,10.0,1,4,18.0,5,4,0.0
1895,1.0,0,32.0,15.0,1,2,14.0,3,4,0.0
1896,1.0,0,22.0,1.5,0,3,17.0,5,5,0.0
1897,1.0,1,27.0,4.0,1,4,17.0,4,4,0.0
1899,1.0,0,52.0,15.0,1,5,14.0,1,5,0.0
1904,1.0,0,27.0,7.0,1,2,12.0,1,2,0.0
1905,1.0,0,27.0,7.0,1,3,12.0,1,4,0.0
1908,1.0,0,42.0,15.0,1,2,14.0,1,4,0.0
1916,1.0,0,42.0,15.0,1,4,14.0,5,4,0.0
1918,1.0,1,27.0,7.0,1,4,14.0,3,3,0.0
1920,1.0,1,27.0,7.0,1,2,20.0,6,2,0.0
1930,1.0,0,42.0,15.0,1,3,12.0,3,3,0.0
1940,1.0,1,27.0,4.0,1,3,16.0,3,5,0.0
1947,1.0,0,27.0,7.0,1,3,14.0,1,4,0.0
1949,1.0,0,22.0,1.5,0,2,14.0,4,5,0.0
1951,1.0,0,27.0,4.0,1,4,14.0,1,4,0.0
1952,1.0,0,22.0,4.0,0,4,14.0,5,5,0.0
1960,1.0,0,22.0,1.5,0,2,16.0,4,5,0.0
9001,1.0,1,47.0,15.0,0,4,14.0,5,4,0.0
9012,1.0,1,37.0,10.0,1,2,18.0,6,2,0.0
9023,1.0,1,37.0,15.0,1,3,17.0,5,4,0.0
9029,1.0,0,27.0,4.0,1,2,16.0,1,4,0.0
6,1.0,1,27.0,1.5,0,3,18.0,4,4,3.0
12,1.0,0,27.0,4.0,1,3,17.0,1,5,3.0
43,1.0,1,37.0,15.0,1,5,18.0,6,2,7.0
53,1.0,0,32.0,10.0,1,3,17.0,5,2,12.0
67,1.0,1,22.0,0.125,0,4,16.0,5,5,1.0
79,1.0,0,22.0,1.5,1,2,14.0,1,5,1.0
122,1.0,1,37.0,15.0,1,4,14.0,5,2,12.0
126,1.0,0,22.0,1.5,0,2,14.0,3,4,7.0
133,1.0,1,37.0,15.0,1,2,18.0,6,4,2.0
138,1.0,0,32.0,15.0,1,4,12.0,3,2,3.0
154,1.0,0,37.0,15.0,1,4,14.0,4,2,1.0
159,1.0,0,42.0,15.0,1,3,17.0,1,4,7.0
174,1.0,0,42.0,15.0,1,5,9.0,4,1,12.0
176,1.0,1,37.0,10.0,1,2,20.0,6,2,12.0
181,1.0,0,32.0,15.0,1,3,14.0,1,2,12.0
182,1.0,1,27.0,4.0,0,1,18.0,6,5,3.0
186,1.0,1,37.0,10.0,1,2,18.0,7,3,7.0
189,1.0,0,27.0,4.0,0,3,17.0,5,5,7.0
204,1.0,1,42.0,15.0,1,4,16.0,5,5,1.0
215,1.0,0,47.0,15.0,1,5,14.0,4,5,1.0
232,1.0,0,27.0,4.0,1,3,18.0,5,4,7.0
233,1.0,0,27.0,7.0,1,5,14.0,1,4,1.0
252,1.0,1,27.0,1.5,1,3,17.0,5,4,12.0
253,1.0,0,27.0,7.0,1,4,14.0,6,2,12.0
274,1.0,0,42.0,15.0,1,4,16.0,5,4,3.0
275,1.0,0,27.0,10.0,1,4,12.0,7,3,7.0
287,1.0,1,27.0,1.5,0,2,18.0,5,2,1.0
288,1.0,1,32.0,4.0,0,4,20.0,6,4,1.0
325,1.0,0,27.0,7.0,1,3,14.0,1,3,1.0
328,1.0,0,32.0,10.0,1,4,14.0,1,4,3.0
344,1.0,1,27.0,4.0,1,2,18.0,7,2,3.0
353,1.0,0,17.5,0.75,0,5,14.0,4,5,1.0
354,1.0,0,32.0,10.0,1,4,18.0,1,5,1.0
367,1.0,0,32.0,7.0,1,2,17.0,6,4,7.0
369,1.0,1,37.0,15.0,1,2,20.0,6,4,7.0
390,1.0,0,37.0,10.0,0,1,20.0,5,3,7.0
392,1.0,0,32.0,10.0,1,2,16.0,5,5,12.0
423,1.0,1,52.0,15.0,1,2,20.0,6,4,7.0
432,1.0,0,42.0,15.0,1,1,12.0,1,3,7.0
436,1.0,1,52.0,15.0,1,2,20.0,6,3,1.0
483,1.0,1,37.0,15.0,1,3,18.0,6,5,2.0
513,1.0,0,22.0,4.0,0,3,12.0,3,4,12.0
516,1.0,1,27.0,7.0,1,1,18.0,6,2,12.0
518,1.0,1,27.0,4.0,1,3,18.0,5,5,1.0
520,1.0,1,47.0,15.0,1,4,17.0,6,5,12.0
526,1.0,0,42.0,15.0,1,4,12.0,1,1,12.0
528,1.0,1,27.0,4.0,0,3,14.0,3,4,7.0
553,1.0,0,32.0,7.0,1,4,18.0,4,5,7.0
576,1.0,1,32.0,0.417,1,3,12.0,3,4,1.0
611,1.0,1,47.0,15.0,1,5,16.0,5,4,3.0
625,1.0,1,37.0,15.0,1,2,20.0,5,4,12.0
635,1.0,1,22.0,4.0,1,2,17.0,6,4,7.0
646,1.0,1,27.0,4.0,0,2,14.0,4,5,1.0
657,1.0,0,52.0,15.0,1,5,16.0,1,3,7.0
659,1.0,1,27.0,4.0,0,3,14.0,3,3,1.0
666,1.0,0,27.0,10.0,1,4,16.0,1,4,1.0
679,1.0,1,32.0,7.0,1,3,14.0,7,4,1.0
729,1.0,1,32.0,7.0,1,2,18.0,4,1,7.0
755,1.0,1,22.0,1.5,0,1,14.0,3,2,3.0
758,1.0,1,22.0,4.0,1,3,18.0,6,4,7.0
770,1.0,1,42.0,15.0,1,4,20.0,6,4,7.0
786,1.0,0,57.0,15.0,1,1,18.0,5,4,2.0
797,1.0,0,32.0,4.0,1,3,18.0,5,2,7.0
811,1.0,1,27.0,4.0,1,1,16.0,4,4,1.0
834,1.0,1,32.0,7.0,1,4,16.0,1,4,7.0
858,1.0,1,57.0,15.0,1,1,17.0,4,4,2.0
885,1.0,0,42.0,15.0,1,4,14.0,5,2,7.0
893,1.0,1,37.0,10.0,1,1,18.0,5,3,7.0
927,1.0,1,42.0,15.0,1,3,17.0,6,1,3.0
928,1.0,0,52.0,15.0,1,3,14.0,4,4,1.0
933,1.0,0,27.0,7.0,1,3,17.0,5,3,2.0
951,1.0,1,32.0,7.0,1,2,12.0,4,2,12.0
968,1.0,1,22.0,4.0,0,4,14.0,2,5,1.0
972,1.0,1,27.0,7.0,1,3,18.0,6,4,3.0
975,1.0,0,37.0,15.0,1,1,18.0,5,5,12.0
977,1.0,0,32.0,15.0,1,3,17.0,1,3,7.0
981,1.0,0,27.0,7.0,0,2,17.0,5,5,7.0
986,1.0,0,32.0,7.0,1,3,17.0,5,3,1.0
1002,1.0,1,32.0,1.5,1,2,14.0,2,4,1.0
1007,1.0,0,42.0,15.0,1,4,14.0,1,2,12.0
1011,1.0,1,32.0,10.0,1,3,14.0,5,4,7.0
1035,1.0,1,37.0,4.0,1,1,20.0,6,3,7.0
1050,1.0,0,27.0,4.0,1,2,16.0,5,3,1.0
1056,1.0,0,42.0,15.0,1,3,14.0,4,3,12.0
1057,1.0,1,27.0,10.0,1,5,20.0,6,5,1.0
1075,1.0,1,37.0,10.0,1,2,20.0,6,2,12.0
1080,1.0,0,27.0,7.0,1,1,14.0,3,3,12.0
1125,1.0,0,27.0,7.0,1,4,12.0,1,2,3.0
1131,1.0,1,32.0,10.0,1,2,14.0,4,4,3.0
1138,1.0,0,17.5,0.75,1,2,12.0,1,3,12.0
1150,1.0,0,32.0,15.0,1,3,18.0,5,4,12.0
1163,1.0,0,22.0,7.0,0,4,14.0,4,3,2.0
1169,1.0,1,32.0,7.0,1,4,20.0,6,5,1.0
1198,1.0,1,27.0,4.0,1,2,18.0,6,2,7.0
1204,1.0,0,22.0,1.5,1,5,14.0,5,3,1.0
1218,1.0,0,32.0,15.0,0,3,17.0,5,1,12.0
1230,1.0,0,42.0,15.0,1,2,12.0,1,2,12.0
1236,1.0,1,42.0,15.0,1,3,20.0,5,4,7.0
1247,1.0,1,32.0,10.0,0,2,18.0,4,2,12.0
1259,1.0,0,32.0,15.0,1,3,9.0,1,1,12.0
1294,1.0,1,57.0,15.0,1,5,20.0,4,5,7.0
1353,1.0,1,47.0,15.0,1,4,20.0,6,4,12.0
1370,1.0,0,42.0,15.0,1,2,17.0,6,3,2.0
1427,1.0,1,37.0,15.0,1,3,17.0,6,3,12.0
1445,1.0,1,37.0,15.0,1,5,17.0,5,2,12.0
1460,1.0,1,27.0,10.0,1,2,20.0,6,4,7.0
1480,1.0,1,37.0,15.0,1,2,16.0,5,4,2.0
1505,1.0,0,32.0,15.0,1,1,14.0,5,2,12.0
1543,1.0,1,32.0,10.0,1,3,17.0,6,3,7.0
1548,1.0,1,37.0,15.0,1,4,18.0,5,1,2.0
1550,1.0,0,27.0,1.5,0,2,17.0,5,5,7.0
1561,1.0,0,47.0,15.0,1,2,17.0,5,2,3.0
1564,1.0,1,37.0,15.0,1,2,17.0,5,4,12.0
1573,1.0,0,27.0,4.0,0,2,14.0,5,5,12.0
1575,1.0,0,27.0,10.0,1,4,14.0,1,5,2.0
1599,1.0,0,22.0,4.0,1,3,16.0,1,3,1.0
1622,1.0,1,52.0,7.0,0,4,16.0,5,5,12.0
1629,1.0,0,27.0,4.0,1,1,16.0,3,5,2.0
1664,1.0,0,37.0,15.0,1,2,17.0,6,4,7.0
1669,1.0,0,27.0,4.0,0,1,17.0,3,1,2.0
1674,1.0,0,17.5,0.75,1,2,12.0,3,5,12.0
1682,1.0,0,32.0,15.0,1,5,18.0,5,4,7.0
1685,1.0,0,22.0,4.0,0,1,16.0,3,5,7.0
1697,1.0,1,32.0,4.0,1,4,18.0,6,4,2.0
1716,1.0,0,22.0,1.5,1,3,18.0,5,2,1.0
1730,1.0,0,42.0,15.0,1,2,17.0,5,4,3.0
1731,1.0,1,32.0,7.0,1,4,16.0,4,4,1.0
1732,1.0,1,37.0,15.0,0,3,14.0,6,2,12.0
1743,1.0,1,42.0,15.0,1,3,16.0,6,3,1.0
1751,1.0,1,27.0,4.0,1,1,18.0,5,4,1.0
1757,1.0,1,37.0,15.0,1,4,20.0,7,3,2.0
1763,1.0,1,37.0,15.0,1,3,20.0,6,4,7.0
1766,1.0,1,22.0,1.5,0,2,12.0,3,3,3.0
1772,1.0,1,32.0,4.0,1,3,20.0,6,2,3.0
1776,1.0,1,32.0,15.0,1,5,20.0,6,5,2.0
1782,1.0,0,52.0,15.0,1,1,18.0,5,5,12.0
1784,1.0,1,47.0,15.0,0,1,18.0,6,5,12.0
1791,1.0,0,32.0,15.0,1,4,16.0,4,4,3.0
1831,1.0,0,32.0,15.0,1,3,14.0,3,2,7.0
1840,1.0,0,27.0,7.0,1,4,16.0,1,2,7.0
1844,1.0,1,42.0,15.0,1,3,18.0,6,2,12.0
1856,1.0,0,42.0,15.0,1,2,14.0,3,2,7.0
1876,1.0,1,27.0,7.0,1,2,17.0,5,4,12.0
1929,1.0,1,32.0,10.0,1,4,14.0,4,3,3.0
1935,1.0,1,47.0,15.0,1,3,16.0,4,2,7.0
1938,1.0,1,22.0,1.5,1,1,12.0,2,5,1.0
1941,1.0,0,32.0,10.0,1,2,18.0,5,4,7.0
1954,1.0,1,32.0,10.0,1,2,17.0,6,5,2.0
1959,1.0,1,22.0,7.0,1,3,18.0,6,2,2.0
9010,1.0,0,32.0,15.0,1,3,14.0,1,5,1.0
1 identifier constant sex age nmarried nchildren religious education occupation rate_marriage naffairs
2 4 1.0 1 37.0 10.0 0 3 18.0 7 4 0.0
3 5 1.0 0 27.0 4.0 0 4 14.0 6 4 0.0
4 11 1.0 0 32.0 15.0 1 1 12.0 1 4 0.0
5 16 1.0 1 57.0 15.0 1 5 18.0 6 5 0.0
6 23 1.0 1 22.0 0.75 0 2 17.0 6 3 0.0
7 29 1.0 0 32.0 1.5 0 2 17.0 5 5 0.0
8 44 1.0 0 22.0 0.75 0 2 12.0 1 3 0.0
9 45 1.0 1 57.0 15.0 1 2 14.0 4 4 0.0
10 47 1.0 0 32.0 15.0 1 4 16.0 1 2 0.0
11 49 1.0 1 22.0 1.5 0 4 14.0 4 5 0.0
12 50 1.0 1 37.0 15.0 1 2 20.0 7 2 0.0
13 55 1.0 1 27.0 4.0 1 4 18.0 6 4 0.0
14 64 1.0 1 47.0 15.0 1 5 17.0 6 4 0.0
15 80 1.0 0 22.0 1.5 0 2 17.0 5 4 0.0
16 86 1.0 0 27.0 4.0 0 4 14.0 5 4 0.0
17 93 1.0 0 37.0 15.0 1 1 17.0 5 5 0.0
18 108 1.0 0 37.0 15.0 1 2 18.0 4 3 0.0
19 114 1.0 0 22.0 0.75 0 3 16.0 5 4 0.0
20 115 1.0 0 22.0 1.5 0 2 16.0 5 5 0.0
21 116 1.0 0 27.0 10.0 1 2 14.0 1 5 0.0
22 123 1.0 0 22.0 1.5 0 2 16.0 5 5 0.0
23 127 1.0 0 22.0 1.5 0 2 16.0 5 5 0.0
24 129 1.0 0 27.0 10.0 1 4 16.0 5 4 0.0
25 134 1.0 0 32.0 10.0 1 3 14.0 1 5 0.0
26 137 1.0 1 37.0 4.0 1 2 20.0 6 4 0.0
27 139 1.0 0 22.0 1.5 0 2 18.0 5 5 0.0
28 147 1.0 0 27.0 7.0 0 4 16.0 1 5 0.0
29 151 1.0 1 42.0 15.0 1 5 20.0 6 4 0.0
30 153 1.0 1 27.0 4.0 1 3 16.0 5 5 0.0
31 155 1.0 0 27.0 4.0 1 3 17.0 5 4 0.0
32 162 1.0 1 42.0 15.0 1 4 20.0 6 3 0.0
33 163 1.0 0 22.0 1.5 0 3 16.0 5 5 0.0
34 165 1.0 1 27.0 0.417 0 4 17.0 6 4 0.0
35 168 1.0 0 42.0 15.0 1 5 14.0 5 4 0.0
36 170 1.0 1 32.0 4.0 1 1 18.0 6 4 0.0
37 172 1.0 0 22.0 1.5 0 4 16.0 5 3 0.0
38 184 1.0 0 42.0 15.0 1 3 12.0 1 4 0.0
39 187 1.0 0 22.0 4.0 0 4 17.0 5 5 0.0
40 192 1.0 1 22.0 1.5 1 1 14.0 3 5 0.0
41 194 1.0 0 22.0 0.75 0 3 16.0 1 5 0.0
42 210 1.0 1 32.0 10.0 1 5 20.0 6 5 0.0
43 217 1.0 1 52.0 15.0 1 5 18.0 6 3 0.0
44 220 1.0 0 22.0 0.417 0 5 14.0 1 4 0.0
45 224 1.0 0 27.0 4.0 1 2 18.0 6 1 0.0
46 227 1.0 0 32.0 7.0 1 5 17.0 5 3 0.0
47 228 1.0 1 22.0 4.0 0 3 16.0 5 5 0.0
48 239 1.0 0 27.0 7.0 1 4 18.0 6 5 0.0
49 241 1.0 0 42.0 15.0 1 2 18.0 5 4 0.0
50 245 1.0 1 27.0 1.5 1 4 16.0 3 5 0.0
51 249 1.0 1 42.0 15.0 1 2 20.0 6 4 0.0
52 262 1.0 0 22.0 0.75 0 5 14.0 3 5 0.0
53 265 1.0 1 32.0 7.0 1 2 20.0 6 4 0.0
54 267 1.0 1 27.0 4.0 1 5 20.0 6 5 0.0
55 269 1.0 1 27.0 10.0 1 4 20.0 6 4 0.0
56 271 1.0 1 22.0 4.0 0 1 18.0 5 5 0.0
57 277 1.0 0 37.0 15.0 1 4 14.0 3 1 0.0
58 290 1.0 1 22.0 1.5 1 5 16.0 4 4 0.0
59 292 1.0 0 37.0 15.0 1 4 17.0 1 5 0.0
60 293 1.0 0 27.0 0.75 0 4 17.0 5 4 0.0
61 295 1.0 1 32.0 10.0 1 4 20.0 6 4 0.0
62 299 1.0 0 47.0 15.0 1 5 14.0 7 2 0.0
63 320 1.0 1 37.0 10.0 1 3 20.0 6 4 0.0
64 321 1.0 0 22.0 0.75 0 2 16.0 5 5 0.0
65 324 1.0 1 27.0 4.0 0 2 18.0 4 5 0.0
66 334 1.0 1 32.0 7.0 0 4 20.0 6 4 0.0
67 351 1.0 1 42.0 15.0 1 2 17.0 3 5 0.0
68 355 1.0 1 37.0 10.0 1 4 20.0 6 4 0.0
69 361 1.0 0 47.0 15.0 1 3 17.0 6 5 0.0
70 362 1.0 0 22.0 1.5 0 5 16.0 5 5 0.0
71 366 1.0 0 27.0 1.5 0 2 16.0 6 4 0.0
72 370 1.0 0 27.0 4.0 0 3 17.0 5 5 0.0
73 374 1.0 0 32.0 10.0 1 5 14.0 4 5 0.0
74 378 1.0 0 22.0 0.125 0 2 12.0 5 5 0.0
75 381 1.0 1 47.0 15.0 1 4 14.0 4 3 0.0
76 382 1.0 1 32.0 15.0 1 1 14.0 5 5 0.0
77 383 1.0 1 27.0 7.0 1 4 16.0 5 5 0.0
78 384 1.0 0 22.0 1.5 1 3 16.0 5 5 0.0
79 400 1.0 1 27.0 4.0 1 3 17.0 6 5 0.0
80 403 1.0 0 22.0 1.5 0 3 16.0 5 5 0.0
81 409 1.0 1 57.0 15.0 1 2 14.0 7 2 0.0
82 412 1.0 1 17.5 1.5 1 3 18.0 6 5 0.0
83 413 1.0 1 57.0 15.0 1 4 20.0 6 5 0.0
84 416 1.0 0 22.0 0.75 0 2 16.0 3 4 0.0
85 418 1.0 1 42.0 4.0 0 4 17.0 3 3 0.0
86 422 1.0 0 22.0 1.5 1 4 12.0 1 5 0.0
87 435 1.0 0 22.0 0.417 0 1 17.0 6 4 0.0
88 439 1.0 0 32.0 15.0 1 4 17.0 5 5 0.0
89 445 1.0 0 27.0 1.5 0 3 18.0 5 2 0.0
90 447 1.0 0 22.0 1.5 1 3 14.0 1 5 0.0
91 448 1.0 0 37.0 15.0 1 3 14.0 1 4 0.0
92 449 1.0 0 32.0 15.0 1 4 14.0 3 4 0.0
93 478 1.0 1 37.0 10.0 1 2 14.0 5 3 0.0
94 482 1.0 1 37.0 10.0 1 4 16.0 5 4 0.0
95 486 1.0 1 57.0 15.0 1 5 20.0 5 3 0.0
96 489 1.0 1 27.0 0.417 0 1 16.0 3 4 0.0
97 490 1.0 0 42.0 15.0 1 5 14.0 1 5 0.0
98 491 1.0 1 57.0 15.0 1 3 16.0 6 1 0.0
99 492 1.0 1 37.0 10.0 1 1 16.0 6 4 0.0
100 503 1.0 1 37.0 15.0 1 3 17.0 5 5 0.0
101 508 1.0 1 37.0 15.0 1 4 20.0 6 5 0.0
102 509 1.0 0 27.0 10.0 1 5 14.0 1 5 0.0
103 512 1.0 1 37.0 10.0 1 2 18.0 6 4 0.0
104 515 1.0 0 22.0 0.125 0 4 12.0 4 5 0.0
105 517 1.0 1 57.0 15.0 1 5 20.0 6 5 0.0
106 532 1.0 0 37.0 15.0 1 4 18.0 6 4 0.0
107 533 1.0 1 22.0 4.0 1 4 14.0 6 4 0.0
108 535 1.0 1 27.0 7.0 1 4 18.0 5 4 0.0
109 537 1.0 1 57.0 15.0 1 4 20.0 5 4 0.0
110 538 1.0 1 32.0 15.0 1 3 14.0 6 3 0.0
111 543 1.0 0 22.0 1.5 0 2 14.0 5 4 0.0
112 547 1.0 0 32.0 7.0 1 4 17.0 1 5 0.0
113 550 1.0 0 37.0 15.0 1 4 17.0 6 5 0.0
114 558 1.0 0 32.0 1.5 0 5 18.0 5 5 0.0
115 571 1.0 1 42.0 10.0 1 5 20.0 7 4 0.0
116 578 1.0 0 27.0 7.0 0 3 16.0 5 4 0.0
117 583 1.0 1 37.0 15.0 0 4 20.0 6 5 0.0
118 586 1.0 1 37.0 15.0 1 4 14.0 3 2 0.0
119 594 1.0 1 32.0 10.0 0 5 18.0 6 4 0.0
120 597 1.0 0 22.0 0.75 0 4 16.0 1 5 0.0
121 602 1.0 0 27.0 7.0 1 4 12.0 2 4 0.0
122 603 1.0 0 27.0 7.0 1 2 16.0 2 5 0.0
123 604 1.0 0 42.0 15.0 1 5 18.0 5 4 0.0
124 612 1.0 1 42.0 15.0 1 4 17.0 5 3 0.0
125 613 1.0 0 27.0 7.0 1 2 16.0 1 2 0.0
126 621 1.0 0 22.0 1.5 0 3 16.0 5 5 0.0
127 627 1.0 1 37.0 15.0 1 5 20.0 6 5 0.0
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602 9010 1.0 0 32.0 15.0 1 3 14.0 1 5 1.0