pre-commit automatic changes and also made changes to test_merge.py file to make pandas namespace consistent

Author: AbhishekChaudharii

doc/source/whatsnew/v3.0.0.rst

@@ -736,10 +736,10 @@ Reshaping
 - Bug in :meth:`DataFrame.join` when a :class:`DataFrame` with a :class:`MultiIndex` would raise an ``AssertionError`` when :attr:`MultiIndex.names` contained ``None``. (:issue:`58721`)
 - Bug in :meth:`DataFrame.merge` where merging on a column containing only ``NaN`` values resulted in an out-of-bounds array access (:issue:`59421`)
 - Bug in :meth:`DataFrame.unstack` producing incorrect results when ``sort=False`` (:issue:`54987`, :issue:`55516`)
+- Bug in :meth:`DataFrame.merge` when merging two dataframes with column dtype as numpy.intc resulting in ValueError: Buffer dtype mismatch, Only on windows (:issue:`60091`)
+- Bug in :meth:`DataFrame.merge` when merging two dataframes with column dtype as numpy.uintc resulting in KeyError: <class 'numpy.uintc'> ,Only on windows (:issue:`58713`)
 - Bug in :meth:`DataFrame.pivot_table` incorrectly subaggregating results when called without an ``index`` argument (:issue:`58722`)
 - Bug in :meth:`DataFrame.unstack` producing incorrect results when manipulating empty :class:`DataFrame` with an :class:`ExtentionDtype` (:issue:`59123`)
-- Bug in :meth:`DataFrame.merge` when merging two dataframes with column dtype as numpy.uintc resulting in KeyError: <class 'numpy.uintc'> ,Only on windows (:issue:`58713`)
-- Bug in :meth:`DataFrame.merge` when merging two dataframes with column dtype as numpy.intc resulting in ValueError: Buffer dtype mismatch, Only on windows (:issue:`60091`)
 
 Sparse
 ^^^^^^

pandas/tests/reshape/merge/test_merge.py

@@ -1844,42 +1844,40 @@ def test_merge_empty(self, left_empty, how, exp):
         tm.assert_frame_equal(result, expected)
 
     def test_merge_with_uintc_columns(self):
-        df1 = pd.DataFrame({"a": ["foo", "bar"], "b": np.array([1, 2], dtype=np.uintc)})
-        df2 = pd.DataFrame({"a": ["foo", "baz"], "b": np.array([3, 4], dtype=np.uintc)})
+        df1 = DataFrame({"a": ["foo", "bar"], "b": np.array([1, 2], dtype=np.uintc)})
+        df2 = DataFrame({"a": ["foo", "baz"], "b": np.array([3, 4], dtype=np.uintc)})
         result = df1.merge(df2, how="outer")
-        expected = pd.DataFrame(
+        expected = DataFrame(
             {
                 "a": ["bar", "baz", "foo", "foo"],
                 "b": np.array([2, 4, 1, 3], dtype=np.uintc),
             }
         )
         tm.assert_frame_equal(result.reset_index(drop=True), expected)
-    
+
     def test_merge_with_intc_columns(self):
-        df1 = pd.DataFrame({"a": ["foo", "bar"], "b": np.array([1, 2], dtype=np.intc)})
-        df2 = pd.DataFrame({"a": ["foo", "baz"], "b": np.array([3, 4], dtype=np.intc)})
+        df1 = DataFrame({"a": ["foo", "bar"], "b": np.array([1, 2], dtype=np.intc)})
+        df2 = DataFrame({"a": ["foo", "baz"], "b": np.array([3, 4], dtype=np.intc)})
         result = df1.merge(df2, how="outer")
-        expected = pd.DataFrame(
+        expected = DataFrame(
             {
                 "a": ["bar", "baz", "foo", "foo"],
                 "b": np.array([2, 4, 1, 3], dtype=np.intc),
             }
         )
         tm.assert_frame_equal(result.reset_index(drop=True), expected)
-    
+
     def test_merge_intc_non_monotonic(self):
-        df = pd.DataFrame({"join_key": pd.Series([0, 2, 1], dtype=np.intc)})
-        df_details = pd.DataFrame({"join_key": pd.Series([0, 1, 2], dtype=np.intc),"value": ["a", "b", "c"]})
-        merged = pd.merge(df, df_details, on="join_key", how="left")
-        expected = pd.DataFrame(
-            {
-                'join_key':np.array([0,2,1],dtype=np.intc),
-                'value':['a','c','b']
-            }
+        df = DataFrame({"join_key": Series([0, 2, 1], dtype=np.intc)})
+        df_details = DataFrame(
+            {"join_key": Series([0, 1, 2], dtype=np.intc), "value": ["a", "b", "c"]}
         )
-        tm.assert_frame_equal(merged.reset_index(drop=True),expected)
-
-        
+        # merged = pd.merge(df, df_details, on="join_key", how="left")
+        merged = df.merge(df_details, on="join_key", how="left")
+        expected = DataFrame(
+            {"join_key": np.array([0, 2, 1], dtype=np.intc), "value": ["a", "c", "b"]}
+        )
+        tm.assert_frame_equal(merged.reset_index(drop=True), expected)
 
 
 @pytest.fixture