Fix Series.to_frame(name=None) setting a None name (#16698)

In pandas 2.0, `to_frame(name=None)` allowed the resulting column name to be `None` pandas-dev/pandas#45523

Looks like based on the current default of `cudf.Series.to_frame`, this behavior was not reflected.

Additionally, created a `SingleColumnFrame._to_frame` to more easily share the logic between `Series.to_frame` and `Index.to_frame`

Authors:
  - Matthew Roeschke (https://github.com/mroeschke)

Approvers:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

URL: #16698

python/cudf/cudf/core/_base_index.py

@@ -798,64 +798,6 @@ def fillna(self, value, downcast=None):
 
         return super().fillna(value=value)
 
-    def to_frame(self, index=True, name=no_default):
-        """Create a DataFrame with a column containing this Index
-
-        Parameters
-        ----------
-        index : boolean, default True
-            Set the index of the returned DataFrame as the original Index
-        name : object, defaults to index.name
-            The passed name should substitute for the index name (if it has
-            one).
-
-        Returns
-        -------
-        DataFrame
-            DataFrame containing the original Index data.
-
-        See Also
-        --------
-        Index.to_series : Convert an Index to a Series.
-        Series.to_frame : Convert Series to DataFrame.
-
-        Examples
-        --------
-        >>> import cudf
-        >>> idx = cudf.Index(['Ant', 'Bear', 'Cow'], name='animal')
-        >>> idx.to_frame()
-               animal
-        animal
-        Ant       Ant
-        Bear     Bear
-        Cow       Cow
-
-        By default, the original Index is reused. To enforce a new Index:
-
-        >>> idx.to_frame(index=False)
-            animal
-        0   Ant
-        1  Bear
-        2   Cow
-
-        To override the name of the resulting column, specify `name`:
-
-        >>> idx.to_frame(index=False, name='zoo')
-            zoo
-        0   Ant
-        1  Bear
-        2   Cow
-        """
-
-        if name is no_default:
-            col_name = 0 if self.name is None else self.name
-        else:
-            col_name = name
-
-        return cudf.DataFrame(
-            {col_name: self._values}, index=self if index else None
-        )
-
     def to_arrow(self):
         """Convert to a suitable Arrow object."""
         raise NotImplementedError

python/cudf/cudf/core/index.py

@@ -529,6 +529,11 @@ def to_pandas(
             name=self.name,
         )
 
+    def to_frame(
+        self, index: bool = True, name: Hashable = no_default
+    ) -> cudf.DataFrame:
+        return self._as_int_index().to_frame(index=index, name=name)
+
     @property
     def is_unique(self) -> bool:
         return True
@@ -1646,6 +1651,58 @@ def to_pandas(
         result.name = self.name
         return result
 
+    def to_frame(
+        self, index: bool = True, name: Hashable = no_default
+    ) -> cudf.DataFrame:
+        """Create a DataFrame with a column containing this Index
+
+        Parameters
+        ----------
+        index : boolean, default True
+            Set the index of the returned DataFrame as the original Index
+        name : object, defaults to index.name
+            The passed name should substitute for the index name (if it has
+            one).
+
+        Returns
+        -------
+        DataFrame
+            DataFrame containing the original Index data.
+
+        See Also
+        --------
+        Index.to_series : Convert an Index to a Series.
+        Series.to_frame : Convert Series to DataFrame.
+
+        Examples
+        --------
+        >>> import cudf
+        >>> idx = cudf.Index(['Ant', 'Bear', 'Cow'], name='animal')
+        >>> idx.to_frame()
+               animal
+        animal
+        Ant       Ant
+        Bear     Bear
+        Cow       Cow
+
+        By default, the original Index is reused. To enforce a new Index:
+
+        >>> idx.to_frame(index=False)
+            animal
+        0   Ant
+        1  Bear
+        2   Cow
+
+        To override the name of the resulting column, specify `name`:
+
+        >>> idx.to_frame(index=False, name='zoo')
+            zoo
+        0   Ant
+        1  Bear
+        2   Cow
+        """
+        return self._to_frame(name=name, index=self if index else None)
+
     def append(self, other):
         if is_list_like(other):
             to_concat = [self]

python/cudf/cudf/core/series.py

@@ -1160,7 +1160,7 @@ def reset_index(
         )
 
     @_performance_tracking
-    def to_frame(self, name=None):
+    def to_frame(self, name: abc.Hashable = no_default) -> cudf.DataFrame:
         """Convert Series into a DataFrame
 
         Parameters
@@ -1192,15 +1192,7 @@ def to_frame(self, name=None):
         13   <NA>
         15      d
         """  # noqa: E501
-
-        if name is not None:
-            col = name
-        elif self.name is None:
-            col = 0
-        else:
-            col = self.name
-
-        return cudf.DataFrame({col: self._column}, index=self.index)
+        return self._to_frame(name=name, index=self.index)
 
     @_performance_tracking
     def memory_usage(self, index=True, deep=False):

python/cudf/cudf/core/single_column_frame.py

@@ -158,6 +158,17 @@ def to_arrow(self) -> pa.Array:
         """
         return self._column.to_arrow()
 
+    def _to_frame(
+        self, name: Hashable, index: cudf.Index | None
+    ) -> cudf.DataFrame:
+        """Helper function for Series.to_frame, Index.to_frame"""
+        if name is no_default:
+            col_name = 0 if self.name is None else self.name
+        else:
+            col_name = name
+        ca = ColumnAccessor({col_name: self._column}, verify=False)
+        return cudf.DataFrame._from_data(ca, index=index)
+
     @property  # type: ignore
     @_performance_tracking
     def is_unique(self) -> bool:

python/cudf/cudf/tests/test_series.py

@@ -2557,6 +2557,13 @@ def test_series_arrow_list_types_roundtrip():
             cudf.from_pandas(pdf)
 
 
+@pytest.mark.parametrize("base_name", [None, "a"])
+def test_series_to_frame_none_name(base_name):
+    result = cudf.Series(range(1), name=base_name).to_frame(name=None)
+    expected = pd.Series(range(1), name=base_name).to_frame(name=None)
+    assert_eq(result, expected)
+
+
 @pytest.mark.parametrize("klass", [cudf.Index, cudf.Series])
 @pytest.mark.parametrize(
     "data", [pa.array([float("nan")]), pa.chunked_array([[float("nan")]])]