feat: add is_null and __invert__ to pyarrow series (#534)

narwhals/_arrow/expr.py

@@ -125,6 +125,9 @@ def __pow__(self, other: ArrowExpr | Any) -> Self:
     def __rpow__(self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__rpow__", other)
 
+    def __invert__(self) -> Self:
+        return reuse_series_implementation(self, "__invert__")
+
     def filter(self, *predicates: Any) -> Self:
         from narwhals._arrow.namespace import ArrowNamespace
 
@@ -183,6 +186,9 @@ def alias(self, name: str) -> Self:
     def null_count(self) -> Self:
         return reuse_series_implementation(self, "null_count", returns_scalar=True)
 
+    def is_null(self) -> Self:
+        return reuse_series_implementation(self, "is_null")
+
     def head(self, n: int) -> Self:
         return reuse_series_implementation(self, "head", n)
 

narwhals/_arrow/series.py

@@ -139,6 +139,10 @@ def __rpow__(self, other: Any) -> Self:
         other = validate_column_comparand(other)
         return self._from_native_series(pc.power(other, ser))
 
+    def __invert__(self) -> Self:
+        pc = get_pyarrow_compute()
+        return self._from_native_series(pc.invert(self._native_series))
+
     def filter(self, other: Any) -> Self:
         other = validate_column_comparand(other)
         return self._from_native_series(self._native_series.filter(other))
@@ -229,6 +233,10 @@ def all(self) -> bool:
     def is_empty(self) -> bool:
         return len(self) == 0
 
+    def is_null(self) -> Self:
+        ser = self._native_series
+        return self._from_native_series(ser.is_null())
+
     def cast(self, dtype: DType) -> Self:
         pc = get_pyarrow_compute()
         ser = self._native_series

tests/frame/test_common.py

@@ -152,10 +152,7 @@ def test_expr_min_max(request: Any, constructor: Any) -> None:
     compare_dicts(result_max, expected_max)
 
 
-def test_expr_na(request: Any, constructor_with_lazy: Any) -> None:
-    if "pyarrow_table" in str(constructor_with_lazy):
-        request.applymarker(pytest.mark.xfail)
-
+def test_expr_na(constructor_with_lazy: Any) -> None:
     df = nw.from_native(constructor_with_lazy(data_na)).lazy()
     result_nna = df.filter((~nw.col("a").is_null()) & (~df.collect()["z"].is_null()))
     expected = {"a": [2], "b": [6], "z": [9]}

utils/check_backend_completeness.py

@@ -25,7 +25,6 @@
     "Series.is_first_distinct",
     "Series.is_in",
     "Series.is_last_distinct",
-    "Series.is_null",
     "Series.is_sorted",
     "Series.is_unique",
     "Series.len",