COMPAT: Use consistent import location for pandas testing

Add pandas testing to compat

Author: bashtage

statsmodels/base/tests/test_generic_methods.py

@@ -10,6 +10,7 @@
 
 Author: Josef Perktold
 """
+from statsmodels.compat.pandas import assert_series_equal, assert_index_equal
 from statsmodels.compat.python import range
 
 import numpy as np
@@ -660,12 +661,6 @@ def test_predict_missing(self):
         ex.iloc[0, 1] = np.nan
         predicted1 = self.res.predict(ex)
         predicted2 = self.res.predict(ex[1:])
-        from pandas.util.testing import assert_series_equal
-        try:
-            from pandas.util.testing import assert_index_equal
-        except ImportError:
-            # for old pandas
-            from numpy.testing import assert_array_equal as assert_index_equal
 
         assert_index_equal(predicted1.index, ex.index)
         assert_series_equal(predicted1[1:], predicted2)

statsmodels/base/tests/test_predict.py

@@ -2,12 +2,12 @@
 """
 Tests for Results.predict
 """
+from statsmodels.compat.pandas import testing as pdt
 
 import numpy as np
 import pandas as pd
 
 from numpy.testing import assert_allclose, assert_equal
-import pandas.util.testing as pdt
 
 from statsmodels.regression.linear_model import OLS
 from statsmodels.genmod.generalized_linear_model import GLM

statsmodels/compat/pandas.py

@@ -29,3 +29,12 @@ def sort_values(df, *args, **kwargs):
 
     data_klasses = (pandas.Series, pandas.DataFrame, pandas.Panel,
                     pandas.WidePanel)
+
+try:
+    import pandas.testing as testing
+except ImportError:
+    import pandas.util.testing as testing
+
+assert_frame_equal = testing.assert_frame_equal
+assert_index_equal = testing.assert_index_equal
+assert_series_equal = testing.assert_series_equal

statsmodels/stats/tests/test_influence.py

@@ -4,15 +4,12 @@
 
 Author: Josef Perktold
 """
+from statsmodels.compat.pandas import testing as pdt
 
 import os.path
 import numpy as np
 from numpy.testing import assert_allclose
 import pandas as pd
-try:
-    import pandas.testing as pdt
-except ImportError:
-    import pandas.util.testing as pdt
 
 import pytest
 

statsmodels/tools/testing.py

@@ -1,12 +1,12 @@
 """assert functions from numpy and pandas testing
 
 """
+from statsmodels.compat.pandas import testing as pdt
 
 import re
 
 import numpy.testing as npt
 import pandas
-import pandas.util.testing as pdt
 
 # for pandas version check
 def strip_rc(version):

statsmodels/tsa/tests/test_stattools.py

@@ -1,3 +1,4 @@
+from statsmodels.compat.pandas import assert_index_equal
 from statsmodels.compat.python import lrange
 
 import os
@@ -752,35 +753,34 @@ def test_innovations_errors():
 def test_innovations_filter_brockwell_davis():
     ma = -0.9
     acovf = np.array([1 + ma ** 2, ma])
-    theta, sigma2 = innovations_algo(acovf, nobs=4)
+    theta, _ = innovations_algo(acovf, nobs=4)
     e = np.random.randn(5)
     endog = e[1:] + ma * e[:-1]
     resid = innovations_filter(endog, theta)
     expected = [endog[0]]
     for i in range(1, 4):
         expected.append(endog[i] + theta[i, 0] * expected[-1])
-    print(expected)
     expected = np.array(expected)
     assert_allclose(resid, expected)
 
 
 def test_innovations_filter_pandas():
     ma = np.array([-0.9, 0.5])
     acovf = np.array([1 + (ma ** 2).sum(), ma[0] + ma[1] * ma[0], ma[1]])
-    theta, sigma2 = innovations_algo(acovf, nobs=10)
+    theta, _ = innovations_algo(acovf, nobs=10)
     endog = np.random.randn(10)
     endog_pd = pd.Series(endog,
                          index=pd.date_range('2000-01-01', periods=10))
     resid = innovations_filter(endog, theta)
     resid_pd = innovations_filter(endog_pd, theta)
     assert_allclose(resid, resid_pd.values)
-    pd.testing.assert_index_equal(endog_pd.index, resid_pd.index)
+    assert_index_equal(endog_pd.index, resid_pd.index)
 
 
 def test_innovations_filter_errors():
     ma = -0.9
     acovf = np.array([1 + ma ** 2, ma])
-    theta, sigma2 = innovations_algo(acovf, nobs=4)
+    theta, _ = innovations_algo(acovf, nobs=4)
     with pytest.raises(ValueError):
         innovations_filter(np.empty((2, 2)), theta)
     with pytest.raises(ValueError):