Pure copy/paste of _check_stat_op and _check_bool_op

Author: h-vetinari

pandas/tests/frame/test_analytics.py

@@ -25,6 +25,147 @@
 import pandas.util._test_decorators as td
 
 
+    def _check_stat_op(self, name, alternative, main_frame, float_frame,
+                       float_string_frame, has_skipna=True,
+                       has_numeric_only=False, check_dtype=True,
+                       check_dates=False, check_less_precise=False,
+                       skipna_alternative=None):
+
+        f = getattr(main_frame, name)
+
+        if check_dates:
+            df = DataFrame({'b': date_range('1/1/2001', periods=2)})
+            _f = getattr(df, name)
+            result = _f()
+            assert isinstance(result, Series)
+
+            df['a'] = lrange(len(df))
+            result = getattr(df, name)()
+            assert isinstance(result, Series)
+            assert len(result)
+
+        if has_skipna:
+            def wrapper(x):
+                return alternative(x.values)
+
+            skipna_wrapper = tm._make_skipna_wrapper(alternative,
+                                                     skipna_alternative)
+            result0 = f(axis=0, skipna=False)
+            result1 = f(axis=1, skipna=False)
+            tm.assert_series_equal(result0, main_frame.apply(wrapper),
+                                   check_dtype=check_dtype,
+                                   check_less_precise=check_less_precise)
+            # HACK: win32
+            tm.assert_series_equal(result1, main_frame.apply(wrapper, axis=1),
+                                   check_dtype=False,
+                                   check_less_precise=check_less_precise)
+        else:
+            skipna_wrapper = alternative
+
+        result0 = f(axis=0)
+        result1 = f(axis=1)
+        tm.assert_series_equal(result0, main_frame.apply(skipna_wrapper),
+                               check_dtype=check_dtype,
+                               check_less_precise=check_less_precise)
+        if name in ['sum', 'prod']:
+            expected = main_frame.apply(skipna_wrapper, axis=1)
+            tm.assert_series_equal(result1, expected, check_dtype=False,
+                                   check_less_precise=check_less_precise)
+
+        # check dtypes
+        if check_dtype:
+            lcd_dtype = main_frame.values.dtype
+            assert lcd_dtype == result0.dtype
+            assert lcd_dtype == result1.dtype
+
+        # bad axis
+        tm.assert_raises_regex(ValueError, 'No axis named 2', f, axis=2)
+        # make sure works on mixed-type frame
+        getattr(float_string_frame, name)(axis=0)
+        getattr(float_string_frame, name)(axis=1)
+
+        if has_numeric_only:
+            getattr(float_string_frame, name)(axis=0, numeric_only=True)
+            getattr(float_string_frame, name)(axis=1, numeric_only=True)
+            getattr(float_frame, name)(axis=0, numeric_only=False)
+            getattr(float_frame, name)(axis=1, numeric_only=False)
+
+        # all NA case
+        if has_skipna:
+            all_na = float_frame * np.NaN
+            r0 = getattr(all_na, name)(axis=0)
+            r1 = getattr(all_na, name)(axis=1)
+            if name in ['sum', 'prod']:
+                unit = int(name == 'prod')
+                expected = pd.Series(unit, index=r0.index, dtype=r0.dtype)
+                tm.assert_series_equal(r0, expected)
+                expected = pd.Series(unit, index=r1.index, dtype=r1.dtype)
+                tm.assert_series_equal(r1, expected)
+
+
+    def _check_bool_op(self, name, alternative, frame, float_string_frame,
+                       has_skipna=True, has_bool_only=False):
+
+        f = getattr(frame, name)
+
+        if has_skipna:
+            def skipna_wrapper(x):
+                nona = x.dropna().values
+                return alternative(nona)
+
+            def wrapper(x):
+                return alternative(x.values)
+
+            result0 = f(axis=0, skipna=False)
+            result1 = f(axis=1, skipna=False)
+            tm.assert_series_equal(result0, frame.apply(wrapper))
+            tm.assert_series_equal(result1, frame.apply(wrapper, axis=1),
+                                   check_dtype=False)  # HACK: win32
+        else:
+            skipna_wrapper = alternative
+            wrapper = alternative
+
+        result0 = f(axis=0)
+        result1 = f(axis=1)
+        tm.assert_series_equal(result0, frame.apply(skipna_wrapper))
+        tm.assert_series_equal(result1, frame.apply(skipna_wrapper, axis=1),
+                               check_dtype=False)
+
+        # bad axis
+        pytest.raises(ValueError, f, axis=2)
+
+        # make sure works on mixed-type frame
+        mixed = float_string_frame
+        mixed['_bool_'] = np.random.randn(len(mixed)) > 0
+        getattr(mixed, name)(axis=0)
+        getattr(mixed, name)(axis=1)
+
+        class NonzeroFail(object):
+
+            def __nonzero__(self):
+                raise ValueError
+
+        mixed['_nonzero_fail_'] = NonzeroFail()
+
+        if has_bool_only:
+            getattr(mixed, name)(axis=0, bool_only=True)
+            getattr(mixed, name)(axis=1, bool_only=True)
+            getattr(frame, name)(axis=0, bool_only=False)
+            getattr(frame, name)(axis=1, bool_only=False)
+
+        # all NA case
+        if has_skipna:
+            all_na = frame * np.NaN
+            r0 = getattr(all_na, name)(axis=0)
+            r1 = getattr(all_na, name)(axis=1)
+            if name == 'any':
+                assert not r0.any()
+                assert not r1.any()
+            else:
+                assert r0.all()
+                assert r1.all()
+
+
 class TestDataFrameAnalytics():
 
     # ---------------------------------------------------------------------=
@@ -803,83 +944,6 @@ def alt(x):
         assert kurt.name is None
         assert kurt2.name == 'bar'
 
-    def _check_stat_op(self, name, alternative, main_frame, float_frame,
-                       float_string_frame, has_skipna=True,
-                       has_numeric_only=False, check_dtype=True,
-                       check_dates=False, check_less_precise=False,
-                       skipna_alternative=None):
-
-        f = getattr(main_frame, name)
-
-        if check_dates:
-            df = DataFrame({'b': date_range('1/1/2001', periods=2)})
-            _f = getattr(df, name)
-            result = _f()
-            assert isinstance(result, Series)
-
-            df['a'] = lrange(len(df))
-            result = getattr(df, name)()
-            assert isinstance(result, Series)
-            assert len(result)
-
-        if has_skipna:
-            def wrapper(x):
-                return alternative(x.values)
-
-            skipna_wrapper = tm._make_skipna_wrapper(alternative,
-                                                     skipna_alternative)
-            result0 = f(axis=0, skipna=False)
-            result1 = f(axis=1, skipna=False)
-            tm.assert_series_equal(result0, main_frame.apply(wrapper),
-                                   check_dtype=check_dtype,
-                                   check_less_precise=check_less_precise)
-            # HACK: win32
-            tm.assert_series_equal(result1, main_frame.apply(wrapper, axis=1),
-                                   check_dtype=False,
-                                   check_less_precise=check_less_precise)
-        else:
-            skipna_wrapper = alternative
-
-        result0 = f(axis=0)
-        result1 = f(axis=1)
-        tm.assert_series_equal(result0, main_frame.apply(skipna_wrapper),
-                               check_dtype=check_dtype,
-                               check_less_precise=check_less_precise)
-        if name in ['sum', 'prod']:
-            expected = main_frame.apply(skipna_wrapper, axis=1)
-            tm.assert_series_equal(result1, expected, check_dtype=False,
-                                   check_less_precise=check_less_precise)
-
-        # check dtypes
-        if check_dtype:
-            lcd_dtype = main_frame.values.dtype
-            assert lcd_dtype == result0.dtype
-            assert lcd_dtype == result1.dtype
-
-        # bad axis
-        tm.assert_raises_regex(ValueError, 'No axis named 2', f, axis=2)
-        # make sure works on mixed-type frame
-        getattr(float_string_frame, name)(axis=0)
-        getattr(float_string_frame, name)(axis=1)
-
-        if has_numeric_only:
-            getattr(float_string_frame, name)(axis=0, numeric_only=True)
-            getattr(float_string_frame, name)(axis=1, numeric_only=True)
-            getattr(float_frame, name)(axis=0, numeric_only=False)
-            getattr(float_frame, name)(axis=1, numeric_only=False)
-
-        # all NA case
-        if has_skipna:
-            all_na = float_frame * np.NaN
-            r0 = getattr(all_na, name)(axis=0)
-            r1 = getattr(all_na, name)(axis=1)
-            if name in ['sum', 'prod']:
-                unit = int(name == 'prod')
-                expected = pd.Series(unit, index=r0.index, dtype=r0.dtype)
-                tm.assert_series_equal(r0, expected)
-                expected = pd.Series(unit, index=r1.index, dtype=r1.dtype)
-                tm.assert_series_equal(r1, expected)
-
     @pytest.mark.parametrize("dropna, expected", [
         (True, {'A': [12],
                 'B': [10.0],
@@ -1336,68 +1400,6 @@ def test_any_all_level_axis_none_raises(self, method):
         with tm.assert_raises_regex(ValueError, xpr):
             getattr(df, method)(axis=None, level='out')
 
-    def _check_bool_op(self, name, alternative, frame, float_string_frame,
-                       has_skipna=True, has_bool_only=False):
-
-        f = getattr(frame, name)
-
-        if has_skipna:
-            def skipna_wrapper(x):
-                nona = x.dropna().values
-                return alternative(nona)
-
-            def wrapper(x):
-                return alternative(x.values)
-
-            result0 = f(axis=0, skipna=False)
-            result1 = f(axis=1, skipna=False)
-            tm.assert_series_equal(result0, frame.apply(wrapper))
-            tm.assert_series_equal(result1, frame.apply(wrapper, axis=1),
-                                   check_dtype=False)  # HACK: win32
-        else:
-            skipna_wrapper = alternative
-            wrapper = alternative
-
-        result0 = f(axis=0)
-        result1 = f(axis=1)
-        tm.assert_series_equal(result0, frame.apply(skipna_wrapper))
-        tm.assert_series_equal(result1, frame.apply(skipna_wrapper, axis=1),
-                               check_dtype=False)
-
-        # bad axis
-        pytest.raises(ValueError, f, axis=2)
-
-        # make sure works on mixed-type frame
-        mixed = float_string_frame
-        mixed['_bool_'] = np.random.randn(len(mixed)) > 0
-        getattr(mixed, name)(axis=0)
-        getattr(mixed, name)(axis=1)
-
-        class NonzeroFail(object):
-
-            def __nonzero__(self):
-                raise ValueError
-
-        mixed['_nonzero_fail_'] = NonzeroFail()
-
-        if has_bool_only:
-            getattr(mixed, name)(axis=0, bool_only=True)
-            getattr(mixed, name)(axis=1, bool_only=True)
-            getattr(frame, name)(axis=0, bool_only=False)
-            getattr(frame, name)(axis=1, bool_only=False)
-
-        # all NA case
-        if has_skipna:
-            all_na = frame * np.NaN
-            r0 = getattr(all_na, name)(axis=0)
-            r1 = getattr(all_na, name)(axis=1)
-            if name == 'any':
-                assert not r0.any()
-                assert not r1.any()
-            else:
-                assert r0.all()
-                assert r1.all()
-
     # ----------------------------------------------------------------------
     # Isin