feat: add DataFrame.rows

docs/api-reference/dataframe.md

@@ -20,6 +20,7 @@
         - null_count
         - pipe
         - rename
+        - rows
         - schema
         - select
         - shape

narwhals/_pandas_like/dataframe.py

@@ -116,6 +116,14 @@ def __getitem__(self, item: str | range | slice) -> PandasSeries | PandasDataFra
     def columns(self) -> list[str]:
         return self._dataframe.columns.tolist()  # type: ignore[no-any-return]
 
+    def rows(
+        self, *, named: bool = False
+    ) -> list[tuple[Any, ...]] | list[dict[str, Any]]:
+        if not named:
+            return list(self._dataframe.itertuples(index=False, name=None))
+
+        return self._dataframe.to_dict("records")  # type: ignore[no-any-return]
+
     def iter_rows(
         self,
         *,

narwhals/dataframe.py

@@ -629,6 +629,67 @@ def columns(self) -> list[str]:
         """
         return super().columns
 
+    @overload
+    def rows(
+        self,
+        *,
+        named: Literal[False],
+    ) -> tuple[Any, ...]: ...
+
+    @overload
+    def rows(
+        self,
+        *,
+        named: Literal[True],
+    ) -> dict[str, Any]: ...
+
+    @overload
+    def rows(
+        self,
+        *,
+        named: bool,
+    ) -> tuple[Any, ...] | dict[str, Any]: ...
+
+    def rows(
+        self,
+        *,
+        named: bool = False,
+    ) -> tuple[Any, ...] | dict[str, Any]:
+        """
+        Returns all data in the DataFrame as a list of rows of python-native values.
+
+        Arguments:
+            named: By default, each row is returned as a tuple of values given
+                in the same order as the frame columns. Setting named=True will
+                return rows of dictionaries instead.
+
+        Examples:
+            >>> import pandas as pd
+            >>> import polars as pl
+            >>> import narwhals as nw
+            >>> df = {"foo": [1, 2, 3], "bar": [6.0, 7.0, 8.0], "ham": ["a", "b", "c"]}
+            >>> df_pd = pd.DataFrame(df)
+            >>> df_pl = pl.DataFrame(df)
+
+            We define a library agnostic function:
+
+            >>> def func(df_any, *, named):
+            ...     df = nw.from_native(df_any)
+            ...     return df.rows(named=named)
+
+            We can then pass either pandas or Polars to `func`:
+
+            >>> func(df_pd, named=False)
+            [(1, 6.0, 'a'), (2, 7.0, 'b'), (3, 8.0, 'c')]
+            >>> func(df_pd, named=True)
+            [{'foo': 1, 'bar': 6.0, 'ham': 'a'}, {'foo': 2, 'bar': 7.0, 'ham': 'b'}, {'foo': 3, 'bar': 8.0, 'ham': 'c'}]
+            >>> func(df_pl, named=False)
+            [(1, 6.0, 'a'), (2, 7.0, 'b'), (3, 8.0, 'c')]
+            >>> func(df_pl, named=True)
+            [{'foo': 1, 'bar': 6.0, 'ham': 'a'}, {'foo': 2, 'bar': 7.0, 'ham': 'b'}, {'foo': 3, 'bar': 8.0, 'ham': 'c'}]
+        """
+        return self._dataframe.rows(named=named)  # type: ignore[no-any-return]
+
     @overload
     def iter_rows(
         self, *, named: Literal[False], buffer_size: int = ...

tests/frame/rows_test.py

@@ -40,6 +40,7 @@
 df_polars_na = pl.DataFrame({"a": [None, 3, 2], "b": [4, 4, 6], "z": [7.0, None, 9]})
 
 
+@pytest.mark.parametrize("method_name", ["iter_rows", "rows"])
 @pytest.mark.parametrize(
     "df_raw", [df_pandas, df_pandas_nullable, df_pandas_pyarrow, df_mpd, df_polars]
 )
@@ -59,6 +60,7 @@
 )
 @pytest.mark.filterwarnings("ignore::FutureWarning")
 def test_rows(
+    method_name: str,
     df_raw: Any,
     named: bool,  # noqa: FBT001
     expected: list[tuple[Any, ...]] | list[dict[str, Any]],
@@ -67,7 +69,7 @@ def test_rows(
     df = nw.DataFrame(df_raw)
 
     # WHEN
-    result = list(df.iter_rows(named=named))
+    result = list(getattr(df, method_name)(named=named))
 
     # THEN
     assert result == expected