CLN: generic tests (pandas-dev#32256)

Author: jbrockmendel

pandas/tests/generic/test_generic.py

@@ -187,8 +187,10 @@ def test_constructor_compound_dtypes(self):
         def f(dtype):
             return self._construct(shape=3, value=1, dtype=dtype)
 
-        msg = "compound dtypes are not implemented"
-        f"in the {self._typ.__name__} constructor"
+        msg = (
+            "compound dtypes are not implemented "
+            f"in the {self._typ.__name__} constructor"
+        )
 
         with pytest.raises(NotImplementedError, match=msg):
             f([("A", "datetime64[h]"), ("B", "str"), ("C", "int32")])

pandas/tests/generic/test_series.py

@@ -24,13 +24,6 @@ class TestSeries(Generic):
     _typ = Series
     _comparator = lambda self, x, y: tm.assert_series_equal(x, y)
 
-    def setup_method(self):
-        self.ts = tm.makeTimeSeries()  # Was at top level in test_series
-        self.ts.name = "ts"
-
-        self.series = tm.makeStringSeries()
-        self.series.name = "series"
-
     def test_rename_mi(self):
         s = Series(
             [11, 21, 31],

pandas/tests/internals/test_internals.py

@@ -203,12 +203,6 @@ def create_mgr(descr, item_shape=None):
 
 class TestBlock:
     def setup_method(self, method):
-        # self.fblock = get_float_ex()  # a,c,e
-        # self.cblock = get_complex_ex() #
-        # self.oblock = get_obj_ex()
-        # self.bool_block = get_bool_ex()
-        # self.int_block = get_int_ex()
-
         self.fblock = create_block("float", [0, 2, 4])
         self.cblock = create_block("complex", [7])
         self.oblock = create_block("object", [1, 3])
@@ -254,22 +248,11 @@ def test_merge(self):
         tm.assert_numpy_array_equal(merged.values[[0, 2]], np.array(avals))
         tm.assert_numpy_array_equal(merged.values[[1, 3]], np.array(bvals))
 
-        # TODO: merge with mixed type?
-
     def test_copy(self):
         cop = self.fblock.copy()
         assert cop is not self.fblock
         assert_block_equal(self.fblock, cop)
 
-    def test_reindex_index(self):
-        pass
-
-    def test_reindex_cast(self):
-        pass
-
-    def test_insert(self):
-        pass
-
     def test_delete(self):
         newb = self.fblock.copy()
         newb.delete(0)
@@ -300,39 +283,7 @@ def test_delete(self):
             newb.delete(3)
 
 
-class TestDatetimeBlock:
-    def test_can_hold_element(self):
-        block = create_block("datetime", [0])
-
-        # We will check that block._can_hold_element iff arr.__setitem__ works
-        arr = pd.array(block.values.ravel())
-
-        # coerce None
-        assert block._can_hold_element(None)
-        arr[0] = None
-        assert arr[0] is pd.NaT
-
-        # coerce different types of datetime objects
-        vals = [np.datetime64("2010-10-10"), datetime(2010, 10, 10)]
-        for val in vals:
-            assert block._can_hold_element(val)
-            arr[0] = val
-
-        val = date(2010, 10, 10)
-        assert not block._can_hold_element(val)
-
-        msg = (
-            "'value' should be a 'Timestamp', 'NaT', "
-            "or array of those. Got 'date' instead."
-        )
-        with pytest.raises(TypeError, match=msg):
-            arr[0] = val
-
-
 class TestBlockManager:
-    def test_constructor_corner(self):
-        pass
-
     def test_attrs(self):
         mgr = create_mgr("a,b,c: f8-1; d,e,f: f8-2")
         assert mgr.nblocks == 2
@@ -441,18 +392,6 @@ def test_set_change_dtype(self, mgr):
         mgr2.set("quux", tm.randn(N))
         assert mgr2.get("quux").dtype == np.float_
 
-    def test_set_change_dtype_slice(self):  # GH8850
-        cols = MultiIndex.from_tuples([("1st", "a"), ("2nd", "b"), ("3rd", "c")])
-        df = DataFrame([[1.0, 2, 3], [4.0, 5, 6]], columns=cols)
-        df["2nd"] = df["2nd"] * 2.0
-
-        blocks = df._to_dict_of_blocks()
-        assert sorted(blocks.keys()) == ["float64", "int64"]
-        tm.assert_frame_equal(
-            blocks["float64"], DataFrame([[1.0, 4.0], [4.0, 10.0]], columns=cols[:2])
-        )
-        tm.assert_frame_equal(blocks["int64"], DataFrame([[3], [6]], columns=cols[2:]))
-
     def test_copy(self, mgr):
         cp = mgr.copy(deep=False)
         for blk, cp_blk in zip(mgr.blocks, cp.blocks):
@@ -486,7 +425,7 @@ def test_sparse_mixed(self):
         assert len(mgr.blocks) == 3
         assert isinstance(mgr, BlockManager)
 
-        # what to test here?
+        # TODO: what to test here?
 
     def test_as_array_float(self):
         mgr = create_mgr("c: f4; d: f2; e: f8")
@@ -650,22 +589,6 @@ def test_interleave(self):
         mgr = create_mgr("a: M8[ns]; b: m8[ns]")
         assert mgr.as_array().dtype == "object"
 
-    def test_interleave_non_unique_cols(self):
-        df = DataFrame(
-            [[pd.Timestamp("20130101"), 3.5], [pd.Timestamp("20130102"), 4.5]],
-            columns=["x", "x"],
-            index=[1, 2],
-        )
-
-        df_unique = df.copy()
-        df_unique.columns = ["x", "y"]
-        assert df_unique.values.shape == df.values.shape
-        tm.assert_numpy_array_equal(df_unique.values[0], df.values[0])
-        tm.assert_numpy_array_equal(df_unique.values[1], df.values[1])
-
-    def test_consolidate(self):
-        pass
-
     def test_consolidate_ordering_issues(self, mgr):
         mgr.set("f", tm.randn(N))
         mgr.set("d", tm.randn(N))
@@ -683,10 +606,6 @@ def test_consolidate_ordering_issues(self, mgr):
             cons.blocks[0].mgr_locs.as_array, np.arange(len(cons.items), dtype=np.int64)
         )
 
-    def test_reindex_index(self):
-        # TODO: should this be pytest.skip?
-        pass
-
     def test_reindex_items(self):
         # mgr is not consolidated, f8 & f8-2 blocks
         mgr = create_mgr("a: f8; b: i8; c: f8; d: i8; e: f8; f: bool; g: f8-2")
@@ -767,13 +686,6 @@ def test_get_bool_data(self):
     def test_unicode_repr_doesnt_raise(self):
         repr(create_mgr("b,\u05d0: object"))
 
-    def test_missing_unicode_key(self):
-        df = DataFrame({"a": [1]})
-        try:
-            df.loc[:, "\u05d0"]  # should not raise UnicodeEncodeError
-        except KeyError:
-            pass  # this is the expected exception
-
     def test_equals(self):
         # unique items
         bm1 = create_mgr("a,b,c: i8-1; d,e,f: i8-2")
@@ -843,8 +755,6 @@ class TestIndexing:
         create_mgr("a,b: f8; c,d: i8; e,f: f8", item_shape=(N, N)),
     ]
 
-    # MANAGERS = [MANAGERS[6]]
-
     @pytest.mark.parametrize("mgr", MANAGERS)
     def test_get_slice(self, mgr):
         def assert_slice_ok(mgr, axis, slobj):
@@ -994,11 +904,6 @@ def assert_reindex_indexer_is_ok(mgr, axis, new_labels, indexer, fill_value):
                     mgr, ax, pd.Index(["foo", "bar", "baz"]), [0, 1, 2], fill_value,
                 )
 
-    # test_get_slice(slice_like, axis)
-    # take(indexer, axis)
-    # reindex_axis(new_labels, axis)
-    # reindex_indexer(new_labels, indexer, axis)
-
 
 class TestBlockPlacement:
     def test_slice_len(self):
@@ -1151,6 +1056,33 @@ def any(self, axis=None):
 
 
 class TestCanHoldElement:
+    def test_datetime_block_can_hold_element(self):
+        block = create_block("datetime", [0])
+
+        # We will check that block._can_hold_element iff arr.__setitem__ works
+        arr = pd.array(block.values.ravel())
+
+        # coerce None
+        assert block._can_hold_element(None)
+        arr[0] = None
+        assert arr[0] is pd.NaT
+
+        # coerce different types of datetime objects
+        vals = [np.datetime64("2010-10-10"), datetime(2010, 10, 10)]
+        for val in vals:
+            assert block._can_hold_element(val)
+            arr[0] = val
+
+        val = date(2010, 10, 10)
+        assert not block._can_hold_element(val)
+
+        msg = (
+            "'value' should be a 'Timestamp', 'NaT', "
+            "or array of those. Got 'date' instead."
+        )
+        with pytest.raises(TypeError, match=msg):
+            arr[0] = val
+
     @pytest.mark.parametrize(
         "value, dtype",
         [
@@ -1280,3 +1212,37 @@ def test_dataframe_not_equal():
     df1 = pd.DataFrame({"a": [1, 2], "b": ["s", "d"]})
     df2 = pd.DataFrame({"a": ["s", "d"], "b": [1, 2]})
     assert df1.equals(df2) is False
+
+
+def test_missing_unicode_key():
+    df = DataFrame({"a": [1]})
+    with pytest.raises(KeyError, match="\u05d0"):
+        df.loc[:, "\u05d0"]  # should not raise UnicodeEncodeError
+
+
+def test_set_change_dtype_slice():
+    # GH#8850
+    cols = MultiIndex.from_tuples([("1st", "a"), ("2nd", "b"), ("3rd", "c")])
+    df = DataFrame([[1.0, 2, 3], [4.0, 5, 6]], columns=cols)
+    df["2nd"] = df["2nd"] * 2.0
+
+    blocks = df._to_dict_of_blocks()
+    assert sorted(blocks.keys()) == ["float64", "int64"]
+    tm.assert_frame_equal(
+        blocks["float64"], DataFrame([[1.0, 4.0], [4.0, 10.0]], columns=cols[:2])
+    )
+    tm.assert_frame_equal(blocks["int64"], DataFrame([[3], [6]], columns=cols[2:]))
+
+
+def test_interleave_non_unique_cols():
+    df = DataFrame(
+        [[pd.Timestamp("20130101"), 3.5], [pd.Timestamp("20130102"), 4.5]],
+        columns=["x", "x"],
+        index=[1, 2],
+    )
+
+    df_unique = df.copy()
+    df_unique.columns = ["x", "y"]
+    assert df_unique.values.shape == df.values.shape
+    tm.assert_numpy_array_equal(df_unique.values[0], df.values[0])
+    tm.assert_numpy_array_equal(df_unique.values[1], df.values[1])