feat: add DuckDB: nw.nth, nw.sum_horizontal, nw.concat_str, group_by with drop_null_keys

narwhals/_arrow/namespace.py

@@ -378,19 +378,19 @@ def concat_str(
         dtypes = import_dtypes_module(self._version)
 
         def func(df: ArrowDataFrame) -> list[ArrowSeries]:
-            series = (
-                s._native_series
-                for _expr in parsed_exprs
-                for s in _expr.cast(dtypes.String())(df)
-            )
+            compliant_series_list = [
+                s for _expr in parsed_exprs for s in _expr.cast(dtypes.String())(df)
+            ]
             null_handling = "skip" if ignore_nulls else "emit_null"
             result_series = pc.binary_join_element_wise(
-                *series, separator, null_handling=null_handling
+                *(s._native_series for s in compliant_series_list),
+                separator,
+                null_handling=null_handling,
             )
             return [
                 ArrowSeries(
                     native_series=result_series,
-                    name="",
+                    name=compliant_series_list[0].name,
                     backend_version=self._backend_version,
                     version=self._version,
                 )

narwhals/_dask/namespace.py

@@ -354,7 +354,7 @@ def func(df: DaskLazyFrame) -> list[dx.Series]:
                     init_value,
                 )
 
-            return [result]
+            return [result.rename(null_mask[0].name)]
 
         return DaskExpr(
             call=func,

narwhals/_duckdb/dataframe.py

@@ -196,10 +196,6 @@ def _from_native_frame(self: Self, df: Any) -> Self:
     def group_by(self: Self, *keys: str, drop_null_keys: bool) -> DuckDBGroupBy:
         from narwhals._duckdb.group_by import DuckDBGroupBy
 
-        if drop_null_keys:
-            msg = "todo"
-            raise NotImplementedError(msg)
-
         return DuckDBGroupBy(
             compliant_frame=self, keys=list(keys), drop_null_keys=drop_null_keys
         )

narwhals/_duckdb/expr.py

@@ -92,6 +92,32 @@ def func(_: DuckDBLazyFrame) -> list[duckdb.Expression]:
             kwargs={},
         )
 
+    @classmethod
+    def from_column_indices(
+        cls: type[Self],
+        *column_indices: int,
+        backend_version: tuple[int, ...],
+        version: Version,
+    ) -> Self:
+        def func(df: DuckDBLazyFrame) -> list[duckdb.Expression]:
+            from duckdb import ColumnExpression
+
+            columns = df.columns
+
+            return [ColumnExpression(columns[i]) for i in column_indices]
+
+        return cls(
+            func,
+            depth=0,
+            function_name="nth",
+            root_names=None,
+            output_names=None,
+            returns_scalar=False,
+            backend_version=backend_version,
+            version=version,
+            kwargs={},
+        )
+
     def _from_call(
         self,
         call: Callable[..., duckdb.Expression],

narwhals/_duckdb/group_by.py

@@ -18,7 +18,10 @@ def __init__(
         keys: list[str],
         drop_null_keys: bool,  # noqa: FBT001
     ) -> None:
-        self._compliant_frame = compliant_frame
+        if drop_null_keys:
+            self._compliant_frame = compliant_frame.drop_nulls(subset=None)
+        else:
+            self._compliant_frame = compliant_frame
         self._keys = keys
 
     def agg(
@@ -46,7 +49,7 @@ def agg(
         try:
             return self._compliant_frame._from_native_frame(
                 self._compliant_frame._native_frame.aggregate(
-                    agg_columns, group_expr=",".join(self._keys)
+                    agg_columns, group_expr=",".join(f'"{key}"' for key in self._keys)
                 )
             )
         except ValueError as exc:  # pragma: no cover

narwhals/_duckdb/namespace.py

@@ -5,6 +5,7 @@
 from functools import reduce
 from typing import TYPE_CHECKING
 from typing import Any
+from typing import Iterable
 from typing import Literal
 from typing import Sequence
 from typing import cast
@@ -74,6 +75,83 @@ def concat(
         )
         return first._from_native_frame(res)
 
+    def concat_str(
+        self,
+        exprs: Iterable[IntoDuckDBExpr],
+        *more_exprs: IntoDuckDBExpr,
+        separator: str,
+        ignore_nulls: bool,
+    ) -> DuckDBExpr:
+        parsed_exprs = [
+            *parse_into_exprs(*exprs, namespace=self),
+            *parse_into_exprs(*more_exprs, namespace=self),
+        ]
+        from duckdb import CaseExpression
+        from duckdb import ConstantExpression
+        from duckdb import FunctionExpression
+
+        def func(df: DuckDBLazyFrame) -> list[duckdb.Expression]:
+            cols = [s for _expr in parsed_exprs for s in _expr(df)]
+            null_mask = [s.isnull() for _expr in parsed_exprs for s in _expr(df)]
+            first_column_name = get_column_name(df, cols[0])
+
+            if not ignore_nulls:
+                null_mask_result = reduce(lambda x, y: x | y, null_mask)
+                cols_separated = [
+                    y
+                    for x in [
+                        (col.cast("string"),)
+                        if i == len(cols) - 1
+                        else (col.cast("string"), ConstantExpression(separator))
+                        for i, col in enumerate(cols)
+                    ]
+                    for y in x
+                ]
+                result = CaseExpression(
+                    condition=~null_mask_result,
+                    value=FunctionExpression("concat", *cols_separated),
+                )
+            else:
+                init_value, *values = [
+                    CaseExpression(~nm, col.cast("string")).otherwise(
+                        ConstantExpression("")
+                    )
+                    for col, nm in zip(cols, null_mask)
+                ]
+                separators = (
+                    CaseExpression(nm, ConstantExpression("")).otherwise(
+                        ConstantExpression(separator)
+                    )
+                    for nm in null_mask[:-1]
+                )
+                result = reduce(
+                    lambda x, y: FunctionExpression("concat", x, y),
+                    (
+                        FunctionExpression("concat", s, v)
+                        for s, v in zip(separators, values)
+                    ),
+                    init_value,
+                )
+
+            return [result.alias(first_column_name)]
+
+        return DuckDBExpr(
+            call=func,
+            depth=max(x._depth for x in parsed_exprs) + 1,
+            function_name="concat_str",
+            root_names=combine_root_names(parsed_exprs),
+            output_names=reduce_output_names(parsed_exprs),
+            returns_scalar=False,
+            backend_version=self._backend_version,
+            version=self._version,
+            kwargs={
+                "exprs": exprs,
+                "more_exprs": more_exprs,
+                "separator": separator,
+                "ignore_nulls": ignore_nulls,
+            },
+        )
+
     def all_horizontal(self, *exprs: IntoDuckDBExpr) -> DuckDBExpr:
         parsed_exprs = parse_into_exprs(*exprs, namespace=self)
 
@@ -158,6 +236,34 @@ def func(df: DuckDBLazyFrame) -> list[duckdb.Expression]:
             kwargs={"exprs": exprs},
         )
 
+    def sum_horizontal(self, *exprs: IntoDuckDBExpr) -> DuckDBExpr:
+        from duckdb import CoalesceOperator
+        from duckdb import ConstantExpression
+
+        parsed_exprs = parse_into_exprs(*exprs, namespace=self)
+
+        def func(df: DuckDBLazyFrame) -> list[duckdb.Expression]:
+            cols = [c for _expr in parsed_exprs for c in _expr(df)]
+            col_name = get_column_name(df, cols[0])
+            return [
+                reduce(
+                    operator.add,
+                    (CoalesceOperator(col, ConstantExpression(0)) for col in cols),
+                ).alias(col_name)
+            ]
+
+        return DuckDBExpr(
+            call=func,
+            depth=max(x._depth for x in parsed_exprs) + 1,
+            function_name="sum_horizontal",
+            root_names=combine_root_names(parsed_exprs),
+            output_names=reduce_output_names(parsed_exprs),
+            returns_scalar=False,
+            backend_version=self._backend_version,
+            version=self._version,
+            kwargs={"exprs": exprs},
+        )
+
     def when(
         self,
         *predicates: IntoDuckDBExpr,
@@ -173,6 +279,11 @@ def col(self, *column_names: str) -> DuckDBExpr:
             *column_names, backend_version=self._backend_version, version=self._version
         )
 
+    def nth(self, *column_indices: int) -> DuckDBExpr:
+        return DuckDBExpr.from_column_indices(
+            *column_indices, backend_version=self._backend_version, version=self._version
+        )
+
     def lit(self, value: Any, dtype: DType | None) -> DuckDBExpr:
         from duckdb import ConstantExpression
 

narwhals/_spark_like/expr.py

@@ -92,6 +92,31 @@ def func(_: SparkLikeLazyFrame) -> list[Column]:
             kwargs={},
         )
 
+    @classmethod
+    def from_column_indices(
+        cls: type[Self],
+        *column_indices: int,
+        backend_version: tuple[int, ...],
+        version: Version,
+    ) -> Self:
+        def func(df: SparkLikeLazyFrame) -> list[Column]:
+            from pyspark.sql import functions as F  # noqa: N812
+
+            columns = df.columns
+            return [F.col(columns[i]) for i in column_indices]
+
+        return cls(
+            func,
+            depth=0,
+            function_name="nth",
+            root_names=None,
+            output_names=None,
+            returns_scalar=False,
+            backend_version=backend_version,
+            version=version,
+            kwargs={},
+        )
+
     def _from_call(
         self,
         call: Callable[..., Column],

narwhals/_spark_like/namespace.py

@@ -53,6 +53,11 @@ def col(self, *column_names: str) -> SparkLikeExpr:
             *column_names, backend_version=self._backend_version, version=self._version
         )
 
+    def nth(self, *column_indices: int) -> SparkLikeExpr:
+        return SparkLikeExpr.from_column_indices(
+            *column_indices, backend_version=self._backend_version, version=self._version
+        )
+
     def lit(self, value: object, dtype: DType | None) -> SparkLikeExpr:
         if dtype is not None:
             msg = "todo"
@@ -293,19 +298,24 @@ def concat_str(
         ]
 
         def func(df: SparkLikeLazyFrame) -> list[Column]:
-            cols = (s.cast(StringType()) for _expr in parsed_exprs for s in _expr(df))
+            cols = [s for _expr in parsed_exprs for s in _expr(df)]
+            cols_casted = [s.cast(StringType()) for s in cols]
             null_mask = [F.isnull(s) for _expr in parsed_exprs for s in _expr(df)]
+            first_column_name = get_column_name(df, cols[0])
 
             if not ignore_nulls:
                 null_mask_result = reduce(lambda x, y: x | y, null_mask)
                 result = F.when(
                     ~null_mask_result,
-                    reduce(lambda x, y: F.format_string(f"%s{separator}%s", x, y), cols),
+                    reduce(
+                        lambda x, y: F.format_string(f"%s{separator}%s", x, y),
+                        cols_casted,
+                    ),
                 ).otherwise(F.lit(None))
             else:
                 init_value, *values = [
                     F.when(~nm, col).otherwise(F.lit(""))
-                    for col, nm in zip(cols, null_mask)
+                    for col, nm in zip(cols_casted, null_mask)
                 ]
 
                 separators = (
@@ -318,7 +328,7 @@ def func(df: SparkLikeLazyFrame) -> list[Column]:
                     init_value,
                 )
 
-            return [result]
+            return [result.alias(first_column_name)]
 
         return SparkLikeExpr(
             call=func,

tests/expr_and_series/all_horizontal_test.py

@@ -57,8 +57,6 @@ def test_allh_nth(
 ) -> None:
     if "polars" in str(constructor) and POLARS_VERSION < (1, 0):
         request.applymarker(pytest.mark.xfail)
-    if ("pyspark" in str(constructor)) or "duckdb" in str(constructor):
-        request.applymarker(pytest.mark.xfail)
     data = {
         "a": [False, False, True],
         "b": [False, True, True],

tests/expr_and_series/concat_str_test.py

@@ -3,6 +3,7 @@
 import pytest
 
 import narwhals.stable.v1 as nw
+from tests.utils import POLARS_VERSION
 from tests.utils import Constructor
 from tests.utils import assert_equal_data
 
@@ -27,7 +28,8 @@ def test_concat_str(
     expected: list[str],
     request: pytest.FixtureRequest,
 ) -> None:
-    if "duckdb" in str(constructor):
+    if "polars" in str(constructor) and POLARS_VERSION < (1, 0, 0):
+        # nth only available after 1.0
         request.applymarker(pytest.mark.xfail)
     df = nw.from_native(constructor(data))
     result = (
@@ -49,16 +51,16 @@ def test_concat_str(
     assert_equal_data(result, {"full_sentence": expected})
     result = (
         df.select(
-            "a",
+            nw.col("a").alias("a_original"),
             nw.concat_str(
-                nw.col("a") * 2,
+                nw.nth(0) * 2,
                 nw.col("b"),
                 nw.col("c"),
                 separator=" ",
                 ignore_nulls=ignore_nulls,  # default behavior is False
-            ).alias("full_sentence"),
+            ),
         )
-        .sort("a")
-        .select("full_sentence")
+        .sort("a_original")
+        .select("a")
     )
-    assert_equal_data(result, {"full_sentence": expected})
+    assert_equal_data(result, {"a": expected})

tests/expr_and_series/dt/datetime_attributes_test.py

@@ -118,7 +118,6 @@ def test_to_date(request: pytest.FixtureRequest, constructor: Constructor) -> No
             "pandas_nullable_constructor",
             "cudf",
             "modin_constructor",
-            "pyspark",
         )
     ):
         request.applymarker(pytest.mark.xfail)

tests/expr_and_series/nth_test.py

@@ -25,8 +25,6 @@ def test_nth(
     expected: dict[str, list[int]],
     request: pytest.FixtureRequest,
 ) -> None:
-    if ("pyspark" in str(constructor)) or "duckdb" in str(constructor):
-        request.applymarker(pytest.mark.xfail)
     if "polars" in str(constructor) and POLARS_VERSION < (1, 0, 0):
         request.applymarker(pytest.mark.xfail)
     df = nw.from_native(constructor(data))