mend

Author: tisjayy

doc/source/whatsnew/v3.0.0.rst

@@ -814,10 +814,7 @@ I/O
 - Bug in :meth:`set_option` where setting the pandas option ``display.html.use_mathjax`` to ``False`` has no effect (:issue:`59884`)
 - Bug in :meth:`to_csv` where ``quotechar``` is not escaped when ``escapechar`` is not None (:issue:`61407`)
 - Bug in :meth:`to_excel` where :class:`MultiIndex` columns would be merged to a single row when ``merge_cells=False`` is passed (:issue:`60274`)
-- Bug in :func:`read_csv` with ``engine="python"`` and callable ``on_bad_lines`` 
-  where a ``ParserWarning`` for extra fields returned by the callable was only 
-  raised when ``index_col`` was ``None``. Now the warning is consistently raised 
-  regardless of ``index_col`` (:issue:`#61837`)
+- Bug in :func:`read_csv` with ``engine="python"`` and callable ``on_bad_lines`` where a ``ParserWarning`` for extra fields returned by the callable was only raised when ``index_col`` was ``None``. Now the warning is consistently raised regardless of ``index_col`` (:issue:`#61837`)
 
 Period
 ^^^^^^

pandas/tests/arithmetic/test_numeric.py

@@ -409,6 +409,25 @@ def test_div_negative_zero(self, zero, numeric_idx, op):
         result = op(idx, zero)
         tm.assert_index_equal(result, expected)
 
+    @pytest.mark.parametrize("dtype", tm.SIGNED_INT_EA_DTYPES)
+def test_numpy_array_mul_extension_array_returns_extension_array(dtype):
+    data = np.arange(10)
+    np_array = np.array(data).reshape(10, 1)
+    ea_array = pd.array(data, dtype=dtype).reshape(10, 1)
+
+    # NumPy array * ExtensionArray
+    result = np_array * ea_array
+
+    # Result should be an ExtensionArray, not a plain NumPy array
+    assert hasattr(result, "dtype")
+    # Check dtype is an ExtensionArray dtype (e.g. Int64Dtype)
+    assert pd.api.types.is_extension_array_dtype(result.dtype)
+
+    # Also verify values match expected multiplication
+    expected = pd.array(data * data, dtype=dtype).reshape(10, 1)
+    tm.assert_extension_array_equal(result.ravel(), expected.ravel())
+
+
     # ------------------------------------------------------------------
 
     @pytest.mark.parametrize("dtype1", [np.int64, np.float64, np.uint64])