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1"""First 100 days of the US House of Representatives 1995"""
2from statsmodels.datasets import utils as du
4__docformat__ = 'restructuredtext'
6COPYRIGHT = """Used with express permission from the original author,
7who retains all rights."""
8TITLE = __doc__
9SOURCE = """
10Jeff Gill's `Generalized Linear Models: A Unifited Approach`
12http://jgill.wustl.edu/research/books.html
13"""
15DESCRSHORT = """Number of bill assignments in the 104th House in 1995"""
17DESCRLONG = """The example in Gill, seeks to explain the number of bill
18assignments in the first 100 days of the US' 104th House of Representatives.
19The response variable is the number of bill assignments in the first 100 days
20over 20 Committees. The explanatory variables in the example are the number of
21assignments in the first 100 days of the 103rd House, the number of members on
22the committee, the number of subcommittees, the log of the number of staff
23assigned to the committee, a dummy variable indicating whether
24the committee is a high prestige committee, and an interaction term between
25the number of subcommittees and the log of the staff size.
27The data returned by load are not cleaned to represent the above example.
28"""
30NOTE = """::
32 Number of Observations - 20
33 Number of Variables - 6
34 Variable name definitions::
36 BILLS104 - Number of bill assignments in the first 100 days of the
37 104th House of Representatives.
38 SIZE - Number of members on the committee.
39 SUBS - Number of subcommittees.
40 STAFF - Number of staff members assigned to the committee.
41 PRESTIGE - PRESTIGE == 1 is a high prestige committee.
42 BILLS103 - Number of bill assignments in the first 100 days of the
43 103rd House of Representatives.
45 Committee names are included as a variable in the data file though not
46 returned by load.
47"""
50def load_pandas():
51 data = _get_data()
52 return du.process_pandas(data, endog_idx=0)
55def load(as_pandas=None):
56 """Load the committee data and returns a data class.
58 Parameters
59 ----------
60 as_pandas : bool
61 Flag indicating whether to return pandas DataFrames and Series
62 or numpy recarrays and arrays. If True, returns pandas.
64 Returns
65 -------
66 Dataset instance:
67 See DATASET_PROPOSAL.txt for more information.
68 """
69 return du.as_numpy_dataset(load_pandas(), as_pandas=as_pandas)
72def _get_data():
73 data = du.load_csv(__file__, 'committee.csv')
74 data = data.iloc[:, 1:7].astype(float)
75 return data