ENH: Added index to output of assert_series_equal on categorical and datetime values (#33575)

Author: amilbourne

pandas/_testing.py

@@ -1024,7 +1024,12 @@ def _raise(left, right, err_msg):
 
 
 def assert_extension_array_equal(
-    left, right, check_dtype=True, check_less_precise=False, check_exact=False
+    left,
+    right,
+    check_dtype=True,
+    check_less_precise=False,
+    check_exact=False,
+    index_values=None,
 ):
     """
     Check that left and right ExtensionArrays are equal.
@@ -1041,6 +1046,8 @@ def assert_extension_array_equal(
         If int, then specify the digits to compare.
     check_exact : bool, default False
         Whether to compare number exactly.
+    index_values : numpy.ndarray, default None
+        optional index (shared by both left and right), used in output.
 
     Notes
     -----
@@ -1056,24 +1063,31 @@ def assert_extension_array_equal(
     if hasattr(left, "asi8") and type(right) == type(left):
         # Avoid slow object-dtype comparisons
         # np.asarray for case where we have a np.MaskedArray
-        assert_numpy_array_equal(np.asarray(left.asi8), np.asarray(right.asi8))
+        assert_numpy_array_equal(
+            np.asarray(left.asi8), np.asarray(right.asi8), index_values=index_values
+        )
         return
 
     left_na = np.asarray(left.isna())
     right_na = np.asarray(right.isna())
-    assert_numpy_array_equal(left_na, right_na, obj="ExtensionArray NA mask")
+    assert_numpy_array_equal(
+        left_na, right_na, obj="ExtensionArray NA mask", index_values=index_values
+    )
 
     left_valid = np.asarray(left[~left_na].astype(object))
     right_valid = np.asarray(right[~right_na].astype(object))
     if check_exact:
-        assert_numpy_array_equal(left_valid, right_valid, obj="ExtensionArray")
+        assert_numpy_array_equal(
+            left_valid, right_valid, obj="ExtensionArray", index_values=index_values
+        )
     else:
         _testing.assert_almost_equal(
             left_valid,
             right_valid,
             check_dtype=check_dtype,
             check_less_precise=check_less_precise,
             obj="ExtensionArray",
+            index_values=index_values,
         )
 
 
@@ -1206,12 +1220,17 @@ def assert_series_equal(
             check_less_precise=check_less_precise,
             check_dtype=check_dtype,
             obj=str(obj),
+            index_values=np.asarray(left.index),
         )
     elif is_extension_array_dtype(left.dtype) and is_extension_array_dtype(right.dtype):
-        assert_extension_array_equal(left._values, right._values)
+        assert_extension_array_equal(
+            left._values, right._values, index_values=np.asarray(left.index)
+        )
     elif needs_i8_conversion(left.dtype) or needs_i8_conversion(right.dtype):
         # DatetimeArray or TimedeltaArray
-        assert_extension_array_equal(left._values, right._values)
+        assert_extension_array_equal(
+            left._values, right._values, index_values=np.asarray(left.index)
+        )
     else:
         _testing.assert_almost_equal(
             left._values,

pandas/tests/util/test_assert_series_equal.py

@@ -165,7 +165,7 @@ def test_series_equal_length_mismatch(check_less_precise):
         tm.assert_series_equal(s1, s2, check_less_precise=check_less_precise)
 
 
-def test_series_equal_values_mismatch(check_less_precise):
+def test_series_equal_numeric_values_mismatch(check_less_precise):
     msg = """Series are different
 
 Series values are different \\(33\\.33333 %\\)
@@ -180,6 +180,38 @@ def test_series_equal_values_mismatch(check_less_precise):
         tm.assert_series_equal(s1, s2, check_less_precise=check_less_precise)
 
 
+def test_series_equal_categorical_values_mismatch(check_less_precise):
+    msg = """Series are different
+
+Series values are different \\(66\\.66667 %\\)
+\\[index\\]: \\[0, 1, 2\\]
+\\[left\\]:  \\[a, b, c\\]
+Categories \\(3, object\\): \\[a, b, c\\]
+\\[right\\]: \\[a, c, b\\]
+Categories \\(3, object\\): \\[a, b, c\\]"""
+
+    s1 = Series(Categorical(["a", "b", "c"]))
+    s2 = Series(Categorical(["a", "c", "b"]))
+
+    with pytest.raises(AssertionError, match=msg):
+        tm.assert_series_equal(s1, s2, check_less_precise=check_less_precise)
+
+
+def test_series_equal_datetime_values_mismatch(check_less_precise):
+    msg = """numpy array are different
+
+numpy array values are different \\(100.0 %\\)
+\\[index\\]: \\[0, 1, 2\\]
+\\[left\\]:  \\[1514764800000000000, 1514851200000000000, 1514937600000000000\\]
+\\[right\\]: \\[1549065600000000000, 1549152000000000000, 1549238400000000000\\]"""
+
+    s1 = Series(pd.date_range("2018-01-01", periods=3, freq="D"))
+    s2 = Series(pd.date_range("2019-02-02", periods=3, freq="D"))
+
+    with pytest.raises(AssertionError, match=msg):
+        tm.assert_series_equal(s1, s2, check_less_precise=check_less_precise)
+
+
 def test_series_equal_categorical_mismatch(check_categorical):
     msg = """Attributes of Series are different