Fix obj arguments in assertions

Author: serl

pandas/_testing/asserters.py

@@ -283,7 +283,7 @@ def _check_types(left, right, obj: str = "Index") -> None:
         right = cast(MultiIndex, right)
 
         for level in range(left.nlevels):
-            lobj = f"MultiIndex level [{level}]"
+            lobj = f"{obj} level [{level}]"
             try:
                 # try comparison on levels/codes to avoid densifying MultiIndex
                 assert_index_equal(
@@ -314,7 +314,7 @@ def _check_types(left, right, obj: str = "Index") -> None:
                     obj=lobj,
                 )
             # get_level_values may change dtype
-            _check_types(left.levels[level], right.levels[level], obj=obj)
+            _check_types(left.levels[level], right.levels[level], obj=lobj)
 
     # skip exact index checking when `check_categorical` is False
     elif check_exact and check_categorical:
@@ -527,7 +527,7 @@ def assert_interval_array_equal(
         kwargs["check_freq"] = False
 
     assert_equal(left._left, right._left, obj=f"{obj}.left", **kwargs)
-    assert_equal(left._right, right._right, obj=f"{obj}.left", **kwargs)
+    assert_equal(left._right, right._right, obj=f"{obj}.right", **kwargs)
 
     assert_attr_equal("closed", left, right, obj=obj)
 

pandas/tests/util/test_assert_frame_equal.py

@@ -79,7 +79,7 @@ def test_frame_equal_shape_mismatch(df1, df2, frame_or_series):
             DataFrame.from_records(
                 {"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
             ),
-            "MultiIndex level \\[0\\] are different",
+            "DataFrame\\.index level \\[0\\] are different",
         ),
     ],
 )

pandas/tests/util/test_assert_index_equal.py

@@ -32,9 +32,9 @@ def test_index_equal_levels_mismatch():
 
 
 def test_index_equal_values_mismatch(check_exact):
-    msg = """MultiIndex level \\[1\\] are different
+    msg = """Index level \\[1\\] are different
 
-MultiIndex level \\[1\\] values are different \\(25\\.0 %\\)
+Index level \\[1\\] values are different \\(25\\.0 %\\)
 \\[left\\]:  Index\\(\\[2, 2, 3, 4\\], dtype='int64'\\)
 \\[right\\]: Index\\(\\[1, 2, 3, 4\\], dtype='int64'\\)"""
 
@@ -172,9 +172,9 @@ def test_index_equal_level_values_mismatch(check_exact, rtol):
     idx2 = MultiIndex.from_tuples([("A", 1), ("A", 2), ("B", 3), ("B", 4)])
     kwargs = {"check_exact": check_exact, "rtol": rtol}
 
-    msg = """MultiIndex level \\[1\\] are different
+    msg = """Index level \\[1\\] are different
 
-MultiIndex level \\[1\\] values are different \\(25\\.0 %\\)
+Index level \\[1\\] values are different \\(25\\.0 %\\)
 \\[left\\]:  Index\\(\\[2, 2, 3, 4\\], dtype='int64'\\)
 \\[right\\]: Index\\(\\[1, 2, 3, 4\\], dtype='int64'\\)"""
 
@@ -311,9 +311,7 @@ def test_assert_multi_index_dtype_check_categorical(check_categorical):
     idx1 = MultiIndex.from_arrays([Categorical(np.array([1, 2], dtype=np.uint64))])
     idx2 = MultiIndex.from_arrays([Categorical(np.array([1, 2], dtype=np.int64))])
     if check_categorical:
-        with pytest.raises(
-            AssertionError, match=r"^MultiIndex level \[0\] are different"
-        ):
+        with pytest.raises(AssertionError, match=r"^Index level \[0\] are different"):
             tm.assert_index_equal(idx1, idx2, check_categorical=check_categorical)
     else:
         tm.assert_index_equal(idx1, idx2, check_categorical=check_categorical)

pandas/tests/util/test_assert_series_equal.py

@@ -137,7 +137,7 @@ def test_less_precise(data1, data2, any_float_dtype, decimals):
             DataFrame.from_records(
                 {"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
             ).c,
-            "MultiIndex level \\[0\\] are different",
+            "Series\\.index level \\[0\\] are different",
         ),
     ],
 )