Move several tests to SharedWithSparse

kernc · kernc · commit 5dcec572dff2 · 2017-07-16T18:52:27.000+02:00
diff --git a/pandas/tests/series/test_api.py b/pandas/tests/series/test_api.py
@@ -1,5 +1,6 @@
 # coding=utf-8
 # pylint: disable-msg=E1101,W0612
+from collections import OrderedDict
 
 import pytest
 
@@ -117,9 +118,78 @@ def test_to_sparse_pass_name(self):
         result = self.ts.to_sparse()
         assert result.name == self.ts.name
 
+    def test_constructor_dict(self):
+        d = {'a': 0., 'b': 1., 'c': 2.}
+        result = self.Series(d)
+        expected = self.Series(d, index=sorted(d.keys()))
+        tm.assert_series_equal(result, expected)
+
+        result = self.Series(d, index=['b', 'c', 'd', 'a'])
+        expected = self.Series([1, 2, np.nan, 0], index=['b', 'c', 'd', 'a'])
+        tm.assert_series_equal(result, expected)
+
+    def test_constructor_subclass_dict(self):
+        data = tm.TestSubDict((x, 10.0 * x) for x in range(10))
+        series = self.Series(data)
+        expected = self.Series(dict(compat.iteritems(data)))
+        tm.assert_series_equal(series, expected)
+
+    def test_constructor_ordereddict(self):
+        # GH3283
+        data = OrderedDict(
+            ('col%s' % i, np.random.random()) for i in range(12))
+
+        series = self.Series(data)
+        expected = self.Series(list(data.values()), list(data.keys()))
+        tm.assert_series_equal(series, expected)
+
+        # Test with subclass
+        class A(OrderedDict):
+            pass
+
+        series = self.Series(A(data))
+        tm.assert_series_equal(series, expected)
+
+    def test_constructor_dict_multiindex(self):
+        d = {('a', 'a'): 0., ('b', 'a'): 1., ('b', 'c'): 2.}
+        _d = sorted(d.items())
+        result = self.Series(d)
+        expected = self.Series(
+            [x[1] for x in _d],
+            index=pd.MultiIndex.from_tuples([x[0] for x in _d]))
+        tm.assert_series_equal(result, expected)
+
+        d['z'] = 111.
+        _d.insert(0, ('z', d['z']))
+        result = self.Series(d)
+        expected = self.Series([x[1] for x in _d],
+                                index=pd.Index([x[0] for x in _d],
+                                               tupleize_cols=False))
+        result = result.reindex(index=expected.index)
+        tm.assert_series_equal(result, expected)
+
+    def test_constructor_dict_timedelta_index(self):
+        # GH #12169 : Resample category data with timedelta index
+        # construct Series from dict as data and TimedeltaIndex as index
+        # will result NaN in result Series data
+        expected = self.Series(
+            data=['A', 'B', 'C'],
+            index=pd.to_timedelta([0, 10, 20], unit='s')
+        )
+
+        result = self.Series(
+            data={pd.to_timedelta(0, unit='s'): 'A',
+                  pd.to_timedelta(10, unit='s'): 'B',
+                  pd.to_timedelta(20, unit='s'): 'C'},
+            index=pd.to_timedelta([0, 10, 20], unit='s')
+        )
+        tm.assert_series_equal(result, expected)
+
 
 class TestSeriesMisc(TestData, SharedWithSparse):
 
+    Series = Series
+
     def test_tab_completion(self):
         # GH 9910
         s = Series(list('abcd'))
diff --git a/pandas/tests/series/test_constructors.py b/pandas/tests/series/test_constructors.py
@@ -605,48 +605,6 @@ def test_constructor_dict(self):
         expected.iloc[1] = 1
         assert_series_equal(result, expected)
 
-    def test_constructor_dict_multiindex(self):
-        check = lambda result, expected: tm.assert_series_equal(
-            result, expected, check_dtype=True, check_series_type=True)
-        d = {('a', 'a'): 0., ('b', 'a'): 1., ('b', 'c'): 2.}
-        _d = sorted(d.items())
-        ser = Series(d)
-        expected = Series([x[1] for x in _d],
-                          index=MultiIndex.from_tuples([x[0] for x in _d]))
-        check(ser, expected)
-
-        d['z'] = 111.
-        _d.insert(0, ('z', d['z']))
-        ser = Series(d)
-        expected = Series([x[1] for x in _d], index=Index(
-            [x[0] for x in _d], tupleize_cols=False))
-        ser = ser.reindex(index=expected.index)
-        check(ser, expected)
-
-    def test_constructor_dict_timedelta_index(self):
-        # GH #12169 : Resample category data with timedelta index
-        # construct Series from dict as data and TimedeltaIndex as index
-        # will result NaN in result Series data
-        expected = Series(
-            data=['A', 'B', 'C'],
-            index=pd.to_timedelta([0, 10, 20], unit='s')
-        )
-
-        result = Series(
-            data={pd.to_timedelta(0, unit='s'): 'A',
-                  pd.to_timedelta(10, unit='s'): 'B',
-                  pd.to_timedelta(20, unit='s'): 'C'},
-            index=pd.to_timedelta([0, 10, 20], unit='s')
-        )
-        # this should work
-        assert_series_equal(result, expected)
-
-    def test_constructor_subclass_dict(self):
-        data = tm.TestSubDict((x, 10.0 * x) for x in range(10))
-        series = Series(data)
-        refseries = Series(dict(compat.iteritems(data)))
-        assert_series_equal(refseries, series)
-
     def test_constructor_dict_datetime64_index(self):
         # GH 9456
 
@@ -670,26 +628,6 @@ def create_data(constructor):
         assert_series_equal(result_datetime, expected)
         assert_series_equal(result_Timestamp, expected)
 
-    def test_orderedDict_ctor(self):
-        # GH3283
-        import pandas
-        import random
-        data = OrderedDict([('col%s' % i, random.random()) for i in range(12)])
-        s = pandas.Series(data)
-        assert all(s.values == list(data.values()))
-
-    def test_orderedDict_subclass_ctor(self):
-        # GH3283
-        import pandas
-        import random
-
-        class A(OrderedDict):
-            pass
-
-        data = A([('col%s' % i, random.random()) for i in range(12)])
-        s = pandas.Series(data)
-        assert all(s.values == list(data.values()))
-
     def test_constructor_list_of_tuples(self):
         data = [(1, 1), (2, 2), (2, 3)]
         s = Series(data)
diff --git a/pandas/tests/sparse/test_series.py b/pandas/tests/sparse/test_series.py
@@ -1,7 +1,6 @@
 # pylint: disable-msg=E1101,W0612
 
 import operator
-from collections import OrderedDict
 from datetime import datetime
 
 import pytest
@@ -61,6 +60,8 @@ def _test_data2_zero():
 
 class TestSparseSeries(SharedWithSparse):
 
+    Series = SparseSeries
+
     def setup_method(self, method):
         arr, index = _test_data1()
 
@@ -1366,61 +1367,6 @@ def test_numpy_func_call(self):
                 getattr(np, func)(getattr(self, series))
 
 
-def test_constructor_dict():
-    d = {'a': 0., 'b': 1., 'c': 2.}
-    result = SparseSeries(d)
-    expected = SparseSeries(d, index=sorted(d.keys()))
-    tm.assert_sp_series_equal(result, expected)
-
-    result = SparseSeries(d, index=['b', 'c', 'd', 'a'])
-    expected = SparseSeries([1, 2, nan, 0], index=['b', 'c', 'd', 'a'])
-    tm.assert_sp_series_equal(result, expected)
-
-
-def test_constructor_dict_multiindex():
-    d = {('a', 'a'): 0., ('b', 'a'): 1., ('b', 'c'): 2.}
-    _d = sorted(d.items())
-    result = SparseSeries(d)
-    expected = SparseSeries(
-        [x[1] for x in _d],
-        index=pd.MultiIndex.from_tuples([x[0] for x in _d]))
-    tm.assert_series_equal(result, expected)
-
-    d['z'] = 111.
-    _d.insert(0, ('z', d['z']))
-    result = SparseSeries(d)
-    expected = SparseSeries([x[1] for x in _d],
-                            index=pd.Index([x[0] for x in _d],
-                                           tupleize_cols=False))
-    result = result.reindex(index=expected.index)
-    tm.assert_series_equal(result, expected)
-
-
-def test_constructor_dict_timedelta_index():
-    # GH #12169 : Resample category data with timedelta index
-    # construct Series from dict as data and TimedeltaIndex as index
-    # will result NaN in result Series data
-    expected = SparseSeries(
-        data=['A', 'B', 'C'],
-        index=pd.to_timedelta([0, 10, 20], unit='s')
-    )
-
-    result = SparseSeries(
-        data={pd.to_timedelta(0, unit='s'): 'A',
-              pd.to_timedelta(10, unit='s'): 'B',
-              pd.to_timedelta(20, unit='s'): 'C'},
-        index=pd.to_timedelta([0, 10, 20], unit='s')
-    )
-    tm.assert_sp_series_equal(result, expected)
-
-
-def test_constructor_subclass_dict():
-    data = tm.TestSubDict((x, 10.0 * x) for x in range(10))
-    series = SparseSeries(data)
-    expected = SparseSeries(dict(compat.iteritems(data)))
-    tm.assert_sp_series_equal(series, expected)
-
-
 @pytest.mark.parametrize(
     'datetime_type', (np.datetime64,
                       pd.Timestamp,
@@ -1434,19 +1380,3 @@ def test_constructor_dict_datetime64_index(datetime_type):
     expected = SparseSeries(values, map(pd.Timestamp, dates))
 
     tm.assert_sp_series_equal(result, expected)
-
-
-def test_orderedDict_ctor():
-    # GH3283
-    data = OrderedDict(('col%s' % i, np.random.random()) for i in range(12))
-
-    series = SparseSeries(data)
-    expected = SparseSeries(list(data.values()), list(data.keys()))
-    tm.assert_sp_series_equal(series, expected)
-
-    # Test with subclass
-    class A(OrderedDict):
-        pass
-
-    series = SparseSeries(A(data))
-    tm.assert_sp_series_equal(series, expected)
