feat: add items, apply methods to DataFrame

bigframes/dataframe.py

@@ -1418,6 +1418,12 @@ def isin(self, values) -> DataFrame:
                 f"isin(), you passed a [{type(values).__name__}]"
             )
 
+    def items(self):
+        column_ids = self._block.value_columns
+        column_labels = self._block.column_labels
+        for col_id, col_label in zip(column_ids, column_labels):
+            yield col_label, bigframes.series.Series(self._block.select_column(col_id))
+
     def dropna(
         self,
         *,
@@ -2382,6 +2388,18 @@ def map(self, func, na_action: Optional[str] = None) -> DataFrame:
             ops.RemoteFunctionOp(func, apply_on_null=(na_action is None))
         )
 
+    def apply(self, func, *, args: typing.Tuple = (), **kwargs):
+        results = {name: func(col, *args, **kwargs) for name, col in self.items()}
+        if all(
+            [
+                isinstance(val, bigframes.series.Series) or utils.is_list_like(val)
+                for val in results.values()
+            ]
+        ):
+            return DataFrame(data=results)
+        else:
+            return pandas.Series(data=results)
+
     def drop_duplicates(
         self,
         subset: typing.Union[blocks.Label, typing.Sequence[blocks.Label]] = None,

tests/system/small/test_dataframe.py

@@ -663,6 +663,57 @@ def test_df_bfill(scalars_dfs):
     pandas.testing.assert_frame_equal(bf_result, pd_result)
 
 
+def test_apply_series_series_callable(
+    scalars_df_index,
+    scalars_pandas_df_index,
+):
+    columns = ["int64_too", "int64_col"]
+
+    def foo(series, arg1, arg2, *, kwarg1=0, kwarg2=0):
+        return series**2 + (arg1 * arg2 % 4) + (kwarg1 * kwarg2 % 7)
+
+    bf_result = (
+        scalars_df_index[columns]
+        .apply(foo, args=(33, 61), kwarg1=52, kwarg2=21)
+        .to_pandas()
+    )
+
+    pd_result = scalars_pandas_df_index[columns].apply(
+        foo, args=(33, 61), kwarg1=52, kwarg2=21
+    )
+
+    pandas.testing.assert_frame_equal(bf_result, pd_result)
+
+
+def test_apply_series_listlike_callable(
+    scalars_df_index,
+    scalars_pandas_df_index,
+):
+    columns = ["int64_too", "int64_col"]
+    bf_result = (
+        scalars_df_index[columns].apply(lambda x: [len(x), x.min(), 24]).to_pandas()
+    )
+
+    pd_result = scalars_pandas_df_index[columns].apply(lambda x: [len(x), x.min(), 24])
+
+    # Convert default pandas dtypes `int64` to match BigQuery DataFrames dtypes.
+    pd_result.index = pd_result.index.astype("Int64")
+    pd_result = pd_result.astype("Int64")
+    pandas.testing.assert_frame_equal(bf_result, pd_result)
+
+
+def test_apply_series_scalar_callable(
+    scalars_df_index,
+    scalars_pandas_df_index,
+):
+    columns = ["int64_too", "int64_col"]
+    bf_result = scalars_df_index[columns].apply(lambda x: x.sum())
+
+    pd_result = scalars_pandas_df_index[columns].apply(lambda x: x.sum())
+
+    pandas.testing.assert_series_equal(bf_result, pd_result)
+
+
 def test_df_isin_list(scalars_dfs):
     scalars_df, scalars_pandas_df = scalars_dfs
     values = ["Hello, World!", 55555, 2.51, pd.NA, True]

third_party/bigframes_vendored/pandas/core/frame.py

@@ -734,6 +734,18 @@ def isin(self, values):
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
+    def items(self):
+        """
+        Iterate over (column name, Series) pairs.
+
+        Iterates over the DataFrame columns, returning a tuple with
+        the column name and the content as a Series.
+
+        Returns:
+            Iterator: Iterator of label, Series for each column.
+        """
+        raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
     # ----------------------------------------------------------------------
     # Sorting
 
@@ -1420,6 +1432,28 @@ def merge(
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
+    def apply(self, func, *, args=(), **kwargs):
+        """Apply a function along an axis of the DataFrame.
+
+        Objects passed to the function are Series objects whose index is
+        the DataFrame's index (``axis=0``) the final return type
+        is inferred from the return type of the applied function.
+
+        Args:
+            func (function):
+                Function to apply to each column or row.
+            args (tuple):
+                Positional arguments to pass to `func` in addition to the
+                array/series.
+            **kwargs:
+                Additional keyword arguments to pass as keywords arguments to
+                `func`.
+
+        Returns:
+            pandas.Series or bigframes.DataFrame: Result of applying ``func`` along the given axis of the DataFrame.
+        """
+        raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
     # ----------------------------------------------------------------------
     # ndarray-like stats methods