211 lines
6.4 KiB
Python
211 lines
6.4 KiB
Python
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import warnings
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import numpy as np
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import pandas as pd
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import pytest
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from numpy.testing import assert_equal
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from statsmodels.iolib.summary2 import summary_col
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from statsmodels.tools.tools import add_constant
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from statsmodels.regression.linear_model import OLS
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class TestSummaryLatex:
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def test_summarycol(self):
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# Test for latex output of summary_col object
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desired = r'''
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\begin{table}
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\caption{}
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\label{}
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\begin{center}
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\begin{tabular}{lll}
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\hline
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& y I & y II \\
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\hline
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const & 7.7500 & 12.4231 \\
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& (1.1058) & (3.1872) \\
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x1 & -0.7500 & -1.5769 \\
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& (0.2368) & (0.6826) \\
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R-squared & 0.7697 & 0.6401 \\
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R-squared Adj. & 0.6930 & 0.5202 \\
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\hline
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\end{tabular}
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\end{center}
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\end{table}
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\bigskip
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Standard errors in parentheses.
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'''
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x = [1, 5, 7, 3, 5]
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x = add_constant(x)
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y1 = [6, 4, 2, 7, 4]
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y2 = [8, 5, 0, 12, 4]
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reg1 = OLS(y1, x).fit()
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reg2 = OLS(y2, x).fit()
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actual = summary_col([reg1, reg2]).as_latex()
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actual = '\n%s\n' % actual
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assert_equal(desired, actual)
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def test_summarycol_float_format(self):
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# Test for latex output of summary_col object
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desired = r"""
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==========================
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y I y II
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--------------------------
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const 7.7 12.4
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(1.1) (3.2)
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x1 -0.7 -1.6
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(0.2) (0.7)
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R-squared 0.8 0.6
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R-squared Adj. 0.7 0.5
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==========================
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Standard errors in
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parentheses.
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""" # noqa:W291
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x = [1, 5, 7, 3, 5]
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x = add_constant(x)
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y1 = [6, 4, 2, 7, 4]
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y2 = [8, 5, 0, 12, 4]
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reg1 = OLS(y1, x).fit()
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reg2 = OLS(y2, x).fit()
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actual = summary_col([reg1, reg2], float_format='%0.1f').as_text()
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actual = '%s\n' % actual
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starred = summary_col([reg1, reg2], stars=True, float_format='%0.1f')
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assert "7.7***" in str(starred)
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assert "12.4**" in str(starred)
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assert "12.4***" not in str(starred)
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assert_equal(actual, desired)
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def test_summarycol_drop_omitted(self):
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# gh-3702
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x = [1, 5, 7, 3, 5]
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x = add_constant(x)
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x2 = np.concatenate([x, np.array([[3], [9], [-1], [4], [0]])], 1)
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y1 = [6, 4, 2, 7, 4]
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y2 = [8, 5, 0, 12, 4]
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reg1 = OLS(y1, x).fit()
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reg2 = OLS(y2, x2).fit()
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actual = summary_col([reg1, reg2], regressor_order=['const', 'x1'],
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drop_omitted=True)
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assert 'x2' not in str(actual)
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actual = summary_col([reg1, reg2], regressor_order=['x1'],
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drop_omitted=False)
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assert 'const' in str(actual)
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assert 'x2' in str(actual)
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def test_summary_col_ordering_preserved(self):
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# gh-3767
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x = [1, 5, 7, 3, 5]
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x = add_constant(x)
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x2 = np.concatenate([x, np.array([[3], [9], [-1], [4], [0]])], 1)
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x2 = pd.DataFrame(x2, columns=['const', 'b', 'a'])
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y1 = [6, 4, 2, 7, 4]
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y2 = [8, 5, 0, 12, 4]
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reg1 = OLS(y1, x2).fit()
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reg2 = OLS(y2, x2).fit()
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info_dict = {'R2': lambda x: f'{int(x.rsquared):.3f}',
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'N': lambda x: f'{int(x.nobs):d}'}
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original = actual = summary_col([reg1, reg2], float_format='%0.4f')
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actual = summary_col([reg1, reg2], regressor_order=['a', 'b'],
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float_format='%0.4f',
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info_dict=info_dict)
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variables = ('const', 'b', 'a')
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for line in str(original).split('\n'):
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for variable in variables:
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if line.startswith(variable):
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assert line in str(actual)
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def test__repr_latex_(self):
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desired = r'''
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\begin{table}
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\caption{}
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\label{}
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\begin{center}
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\begin{tabular}{lll}
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\hline
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& y I & y II \\
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\hline
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const & 7.7500 & 12.4231 \\
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& (1.1058) & (3.1872) \\
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x1 & -0.7500 & -1.5769 \\
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& (0.2368) & (0.6826) \\
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R-squared & 0.7697 & 0.6401 \\
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R-squared Adj. & 0.6930 & 0.5202 \\
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\hline
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\end{tabular}
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\end{center}
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\end{table}
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\bigskip
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Standard errors in parentheses.
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'''
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x = [1, 5, 7, 3, 5]
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x = add_constant(x)
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y1 = [6, 4, 2, 7, 4]
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y2 = [8, 5, 0, 12, 4]
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reg1 = OLS(y1, x).fit()
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reg2 = OLS(y2, x).fit()
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actual = summary_col([reg1, reg2])._repr_latex_()
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actual = '\n%s\n' % actual
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assert_equal(actual, desired)
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def test_OLSsummary(self):
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# Test that latex output of regular OLS output still contains
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# multiple tables
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x = [1, 5, 7, 3, 5]
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x = add_constant(x)
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y1 = [6, 4, 2, 7, 4]
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reg1 = OLS(y1, x).fit()
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with warnings.catch_warnings():
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warnings.simplefilter("ignore")
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actual = reg1.summary().as_latex()
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string_to_find = r'''\end{tabular}
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\begin{tabular}'''
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result = string_to_find in actual
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assert (result is True)
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def test_ols_summary_rsquared_label():
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# Check that the "uncentered" label is correctly added after rsquared
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x = [1, 5, 7, 3, 5, 2, 5, 3]
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y = [6, 4, 2, 7, 4, 9, 10, 2]
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reg_with_constant = OLS(y, add_constant(x)).fit()
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r2_str = 'R-squared:'
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with pytest.warns(UserWarning):
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assert r2_str in str(reg_with_constant.summary2())
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with pytest.warns(UserWarning):
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assert r2_str in str(reg_with_constant.summary())
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reg_without_constant = OLS(y, x, hasconst=False).fit()
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r2_str = 'R-squared (uncentered):'
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with pytest.warns(UserWarning):
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assert r2_str in str(reg_without_constant.summary2())
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with pytest.warns(UserWarning):
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assert r2_str in str(reg_without_constant.summary())
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class TestSummaryLabels:
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"""
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Test that the labels are correctly set in the summary table"""
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@classmethod
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def setup_class(cls):
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y = [1, 1, 4, 2] * 4
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x = add_constant([1, 2, 3, 4] * 4)
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cls.mod = OLS(endog=y, exog=x).fit()
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def test_summary_col_r2(self,):
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# GH 6578
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table = summary_col(results=self.mod, include_r2=True)
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assert "R-squared " in str(table)
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assert "R-squared Adj." in str(table)
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def test_absence_of_r2(self,):
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table = summary_col(results=self.mod, include_r2=False)
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assert "R-squared" not in str(table)
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assert "R-squared Adj." not in str(table)
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