Merge branch 'main' into docstring

Author: zhangbowen-coder

pandas/core/col.py

@@ -39,6 +39,10 @@
     "__ne__": "!=",
     "__and__": "&",
     "__rand__": "&",
+    "__or__": "|",
+    "__ror__": "|",
+    "__xor__": "^",
+    "__rxor__": "^",
 }
 
 
@@ -159,12 +163,28 @@ def __mod__(self, other: Any) -> Expression:
     def __rmod__(self, other: Any) -> Expression:
         return self._with_binary_op("__rmod__", other)
 
+    # Logical ops
     def __and__(self, other: Any) -> Expression:
         return self._with_binary_op("__and__", other)
 
     def __rand__(self, other: Any) -> Expression:
         return self._with_binary_op("__rand__", other)
 
+    def __or__(self, other: Any) -> Expression:
+        return self._with_binary_op("__or__", other)
+
+    def __ror__(self, other: Any) -> Expression:
+        return self._with_binary_op("__ror__", other)
+
+    def __xor__(self, other: Any) -> Expression:
+        return self._with_binary_op("__xor__", other)
+
+    def __rxor__(self, other: Any) -> Expression:
+        return self._with_binary_op("__rxor__", other)
+
+    def __invert__(self) -> Expression:
+        return Expression(lambda df: ~self(df), f"(~{self._repr_str})")
+
     def __array_ufunc__(
         self, ufunc: Callable[..., Any], method: str, *inputs: Any, **kwargs: Any
     ) -> Expression:

pandas/tests/test_col.py

@@ -127,3 +127,65 @@ def mean(self):
         result = df.assign(b=pd.col("a").xyz.mean())
     expected = pd.DataFrame({"a": [1, 2, 3], "b": [2.0, 2.0, 2.0]})
     tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    ("expr", "expected_values", "expected_str"),
+    [
+        (
+            pd.col("a") & pd.col("b"),
+            [False, False, True, False],
+            "(col('a') & col('b'))",
+        ),
+        (
+            pd.col("a") & True,
+            [True, False, True, False],
+            "(col('a') & True)",
+        ),
+        (
+            pd.col("a") | pd.col("b"),
+            [True, True, True, True],
+            "(col('a') | col('b'))",
+        ),
+        (
+            pd.col("a") | False,
+            [True, False, True, False],
+            "(col('a') | False)",
+        ),
+        (
+            pd.col("a") ^ pd.col("b"),
+            [True, True, False, True],
+            "(col('a') ^ col('b'))",
+        ),
+        (
+            pd.col("a") ^ True,
+            [False, True, False, True],
+            "(col('a') ^ True)",
+        ),
+        (
+            ~pd.col("a"),
+            [False, True, False, True],
+            "(~col('a'))",
+        ),
+    ],
+)
+def test_col_logical_ops(
+    expr: Expression, expected_values: list[bool], expected_str: str
+) -> None:
+    # https://github.com/pandas-dev/pandas/issues/63322
+    df = pd.DataFrame({"a": [True, False, True, False], "b": [False, True, True, True]})
+    result = df.assign(c=expr)
+    expected = pd.DataFrame(
+        {
+            "a": [True, False, True, False],
+            "b": [False, True, True, True],
+            "c": expected_values,
+        }
+    )
+    tm.assert_frame_equal(result, expected)
+    assert str(expr) == expected_str
+
+    # Test that the expression works with .loc
+    result = df.loc[expr]
+    expected = df[expected_values]
+    tm.assert_frame_equal(result, expected)