ENH: .equals for Extension Arrays (pandas-dev#30652)

Co-authored-by: Joris Van den Bossche <[email protected]>

Author: 2 people

doc/source/reference/extensions.rst

@@ -45,6 +45,7 @@ objects.
       api.extensions.ExtensionArray.copy
       api.extensions.ExtensionArray.view
       api.extensions.ExtensionArray.dropna
+      api.extensions.ExtensionArray.equals
       api.extensions.ExtensionArray.factorize
       api.extensions.ExtensionArray.fillna
       api.extensions.ExtensionArray.isna

doc/source/whatsnew/v1.1.0.rst

@@ -150,6 +150,8 @@ Other enhancements
   such as ``dict`` and ``list``, mirroring the behavior of :meth:`DataFrame.update` (:issue:`33215`)
 - :meth:`~pandas.core.groupby.GroupBy.transform` and :meth:`~pandas.core.groupby.GroupBy.aggregate` has gained ``engine`` and ``engine_kwargs`` arguments that supports executing functions with ``Numba`` (:issue:`32854`, :issue:`33388`)
 - :meth:`~pandas.core.resample.Resampler.interpolate` now supports SciPy interpolation method :class:`scipy.interpolate.CubicSpline` as method ``cubicspline`` (:issue:`33670`)
+- The ``ExtensionArray`` class has now an :meth:`~pandas.arrays.ExtensionArray.equals`
+  method, similarly to :meth:`Series.equals` (:issue:`27081`).
 -
 
 .. ---------------------------------------------------------------------------

pandas/_testing.py

@@ -1490,7 +1490,9 @@ def box_expected(expected, box_cls, transpose=True):
     -------
     subclass of box_cls
     """
-    if box_cls is pd.Index:
+    if box_cls is pd.array:
+        expected = pd.array(expected)
+    elif box_cls is pd.Index:
         expected = pd.Index(expected)
     elif box_cls is pd.Series:
         expected = pd.Series(expected)

pandas/core/arrays/base.py

@@ -58,6 +58,7 @@ class ExtensionArray:
     dropna
     factorize
     fillna
+    equals
     isna
     ravel
     repeat
@@ -84,6 +85,7 @@ class ExtensionArray:
     * _from_factorized
     * __getitem__
     * __len__
+    * __eq__
     * dtype
     * nbytes
     * isna
@@ -333,6 +335,24 @@ def __iter__(self):
         for i in range(len(self)):
             yield self[i]
 
+    def __eq__(self, other: Any) -> ArrayLike:
+        """
+        Return for `self == other` (element-wise equality).
+        """
+        # Implementer note: this should return a boolean numpy ndarray or
+        # a boolean ExtensionArray.
+        # When `other` is one of Series, Index, or DataFrame, this method should
+        # return NotImplemented (to ensure that those objects are responsible for
+        # first unpacking the arrays, and then dispatch the operation to the
+        # underlying arrays)
+        raise AbstractMethodError(self)
+
+    def __ne__(self, other: Any) -> ArrayLike:
+        """
+        Return for `self != other` (element-wise in-equality).
+        """
+        return ~(self == other)
+
     def to_numpy(
         self, dtype=None, copy: bool = False, na_value=lib.no_default
     ) -> np.ndarray:
@@ -682,6 +702,38 @@ def searchsorted(self, value, side="left", sorter=None):
         arr = self.astype(object)
         return arr.searchsorted(value, side=side, sorter=sorter)
 
+    def equals(self, other: "ExtensionArray") -> bool:
+        """
+        Return if another array is equivalent to this array.
+
+        Equivalent means that both arrays have the same shape and dtype, and
+        all values compare equal. Missing values in the same location are
+        considered equal (in contrast with normal equality).
+
+        Parameters
+        ----------
+        other : ExtensionArray
+            Array to compare to this Array.
+
+        Returns
+        -------
+        boolean
+            Whether the arrays are equivalent.
+        """
+        if not type(self) == type(other):
+            return False
+        elif not self.dtype == other.dtype:
+            return False
+        elif not len(self) == len(other):
+            return False
+        else:
+            equal_values = self == other
+            if isinstance(equal_values, ExtensionArray):
+                # boolean array with NA -> fill with False
+                equal_values = equal_values.fillna(False)
+            equal_na = self.isna() & other.isna()
+            return (equal_values | equal_na).all().item()
+
     def _values_for_factorize(self) -> Tuple[np.ndarray, Any]:
         """
         Return an array and missing value suitable for factorization.
@@ -1134,7 +1186,7 @@ class ExtensionScalarOpsMixin(ExtensionOpsMixin):
     """
 
     @classmethod
-    def _create_method(cls, op, coerce_to_dtype=True):
+    def _create_method(cls, op, coerce_to_dtype=True, result_dtype=None):
         """
         A class method that returns a method that will correspond to an
         operator for an ExtensionArray subclass, by dispatching to the
@@ -1202,7 +1254,7 @@ def _maybe_convert(arr):
                         # exception raised in _from_sequence; ensure we have ndarray
                         res = np.asarray(arr)
                 else:
-                    res = np.asarray(arr)
+                    res = np.asarray(arr, dtype=result_dtype)
                 return res
 
             if op.__name__ in {"divmod", "rdivmod"}:
@@ -1220,4 +1272,4 @@ def _create_arithmetic_method(cls, op):
 
     @classmethod
     def _create_comparison_method(cls, op):
-        return cls._create_method(op, coerce_to_dtype=False)
+        return cls._create_method(op, coerce_to_dtype=False, result_dtype=bool)

pandas/core/arrays/interval.py

@@ -606,9 +606,6 @@ def __eq__(self, other):
 
         return result
 
-    def __ne__(self, other):
-        return ~self.__eq__(other)
-
     def fillna(self, value=None, method=None, limit=None):
         """
         Fill NA/NaN values using the specified method.

pandas/core/internals/blocks.py

@@ -1864,6 +1864,9 @@ def where(
 
         return [self.make_block_same_class(result, placement=self.mgr_locs)]
 
+    def equals(self, other) -> bool:
+        return self.values.equals(other.values)
+
     def _unstack(self, unstacker, fill_value, new_placement):
         # ExtensionArray-safe unstack.
         # We override ObjectBlock._unstack, which unstacks directly on the

pandas/tests/arrays/integer/test_comparison.py

@@ -104,3 +104,13 @@ def test_compare_to_int(self, any_nullable_int_dtype, all_compare_operators):
         expected[s2.isna()] = pd.NA
 
         self.assert_series_equal(result, expected)
+
+
+def test_equals():
+    # GH-30652
+    # equals is generally tested in /tests/extension/base/methods, but this
+    # specifically tests that two arrays of the same class but different dtype
+    # do not evaluate equal
+    a1 = pd.array([1, 2, None], dtype="Int64")
+    a2 = pd.array([1, 2, None], dtype="Int32")
+    assert a1.equals(a2) is False

pandas/tests/extension/base/methods.py

@@ -421,3 +421,32 @@ def test_repeat_raises(self, data, repeats, kwargs, error, msg, use_numpy):
                 np.repeat(data, repeats, **kwargs)
             else:
                 data.repeat(repeats, **kwargs)
+
+    @pytest.mark.parametrize("box", [pd.array, pd.Series, pd.DataFrame])
+    def test_equals(self, data, na_value, as_series, box):
+        data2 = type(data)._from_sequence([data[0]] * len(data), dtype=data.dtype)
+        data_na = type(data)._from_sequence([na_value] * len(data), dtype=data.dtype)
+
+        data = tm.box_expected(data, box, transpose=False)
+        data2 = tm.box_expected(data2, box, transpose=False)
+        data_na = tm.box_expected(data_na, box, transpose=False)
+
+        # we are asserting with `is True/False` explicitly, to test that the
+        # result is an actual Python bool, and not something "truthy"
+
+        assert data.equals(data) is True
+        assert data.equals(data.copy()) is True
+
+        # unequal other data
+        assert data.equals(data2) is False
+        assert data.equals(data_na) is False
+
+        # different length
+        assert data[:2].equals(data[:3]) is False
+
+        # emtpy are equal
+        assert data[:0].equals(data[:0]) is True
+
+        # other types
+        assert data.equals(None) is False
+        assert data[[0]].equals(data[0]) is False

pandas/tests/extension/base/ops.py

@@ -139,10 +139,8 @@ class BaseComparisonOpsTests(BaseOpsUtil):
     def _compare_other(self, s, data, op_name, other):
         op = self.get_op_from_name(op_name)
         if op_name == "__eq__":
-            assert getattr(data, op_name)(other) is NotImplemented
             assert not op(s, other).all()
         elif op_name == "__ne__":
-            assert getattr(data, op_name)(other) is NotImplemented
             assert op(s, other).all()
 
         else:
@@ -176,6 +174,12 @@ def test_direct_arith_with_series_returns_not_implemented(self, data):
         else:
             raise pytest.skip(f"{type(data).__name__} does not implement __eq__")
 
+        if hasattr(data, "__ne__"):
+            result = data.__ne__(other)
+            assert result is NotImplemented
+        else:
+            raise pytest.skip(f"{type(data).__name__} does not implement __ne__")
+
 
 class BaseUnaryOpsTests(BaseOpsUtil):
     def test_invert(self, data):

pandas/tests/extension/json/array.py

@@ -105,6 +105,12 @@ def __setitem__(self, key, value):
     def __len__(self) -> int:
         return len(self.data)
 
+    def __eq__(self, other):
+        return NotImplemented
+
+    def __ne__(self, other):
+        return NotImplemented
+
     def __array__(self, dtype=None):
         if dtype is None:
             dtype = object

pandas/tests/extension/json/test_json.py

@@ -262,6 +262,10 @@ def test_where_series(self, data, na_value):
     def test_searchsorted(self, data_for_sorting):
         super().test_searchsorted(data_for_sorting)
 
+    @pytest.mark.skip(reason="Can't compare dicts.")
+    def test_equals(self, data, na_value, as_series):
+        pass
+
 
 class TestCasting(BaseJSON, base.BaseCastingTests):
     @pytest.mark.skip(reason="failing on np.array(self, dtype=str)")

pandas/tests/extension/test_numpy.py

@@ -276,6 +276,12 @@ def test_repeat(self, data, repeats, as_series, use_numpy):
     def test_diff(self, data, periods):
         return super().test_diff(data, periods)
 
+    @skip_nested
+    @pytest.mark.parametrize("box", [pd.array, pd.Series, pd.DataFrame])
+    def test_equals(self, data, na_value, as_series, box):
+        # Fails creating with _from_sequence
+        super().test_equals(data, na_value, as_series, box)
+
 
 @skip_nested
 class TestArithmetics(BaseNumPyTests, base.BaseArithmeticOpsTests):

pandas/tests/extension/test_sparse.py

@@ -316,6 +316,11 @@ def test_shift_0_periods(self, data):
         data._sparse_values[0] = data._sparse_values[1]
         assert result._sparse_values[0] != result._sparse_values[1]
 
+    @pytest.mark.parametrize("box", [pd.array, pd.Series, pd.DataFrame])
+    def test_equals(self, data, na_value, as_series, box):
+        self._check_unsupported(data)
+        super().test_equals(data, na_value, as_series, box)
+
 
 class TestCasting(BaseSparseTests, base.BaseCastingTests):
     def test_astype_object_series(self, all_data):