Add 'name' as argument for index 'to_frame' method

doc/source/whatsnew/v0.24.0.txt

@@ -184,6 +184,7 @@ Other Enhancements
 - :class:`DatetimeIndex` gained :attr:`DatetimeIndex.timetz` attribute. Returns local time with timezone information. (:issue:`21358`)
 - :class:`Resampler` now is iterable like :class:`GroupBy` (:issue:`15314`).
 - :meth:`Series.resample` and :meth:`DataFrame.resample` have gained the :meth:`Resampler.quantile` (:issue:`15023`).
+- :meth:`Index.to_frame` now supports overriding column name(s) (:issue:`22580`).
 
 .. _whatsnew_0240.api_breaking:
 

pandas/core/indexes/base.py

@@ -1115,17 +1115,21 @@ def to_series(self, index=None, name=None):
 
         return Series(self._to_embed(), index=index, name=name)
 
-    def to_frame(self, index=True):
+    def to_frame(self, index=True, name=None):
         """
         Create a DataFrame with a column containing the Index.
 
-        .. versionadded:: 0.21.0
+        .. versionadded:: 0.24.0
 
         Parameters
         ----------
         index : boolean, default True
             Set the index of the returned DataFrame as the original Index.
 
+        name : object, default None
+            The passed name should substitute for the index name (if it has
+            one).
+
         Returns
         -------
         DataFrame
@@ -1153,10 +1157,19 @@ def to_frame(self, index=True):
         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
         """
 
         from pandas import DataFrame
-        name = self.name or 0
+        if name is None:
+            name = self.name or 0
         result = DataFrame({name: self.values.copy()})
 
         if index:

pandas/core/indexes/multi.py

@@ -1126,27 +1126,42 @@ def _to_safe_for_reshape(self):
         """ convert to object if we are a categorical """
         return self.set_levels([i._to_safe_for_reshape() for i in self.levels])
 
-    def to_frame(self, index=True):
+    def to_frame(self, index=True, name=None):
         """
         Create a DataFrame with the levels of the MultiIndex as columns.
 
-        .. versionadded:: 0.20.0
+        .. versionadded:: 0.24.0
 
         Parameters
         ----------
         index : boolean, default True
             Set the index of the returned DataFrame as the original MultiIndex.
 
+        name : list / sequence of strings, optional
+            The passed names should substitute index level names.
+
         Returns
         -------
         DataFrame : a DataFrame containing the original MultiIndex data.
         """
 
         from pandas import DataFrame
+        if name is not None:
+            if not is_list_like(name):
+                raise TypeError("'name' must be a list / sequence "
+                                "of array-likes.")
+
+            if len(name) != len(self.levels):
+                raise ValueError("'name' should have same length as "
+                                 "number of levels on index")
+            idx_names = name
+        else:
+            idx_names = self.names
+
         result = DataFrame({(name or level):
                             self._get_level_values(level)
                             for name, level in
-                            zip(self.names, range(len(self.levels)))},
+                            zip(idx_names, range(len(self.levels)))},
                            copy=False)
         if index:
             result.index = self

pandas/tests/indexes/common.py

@@ -81,6 +81,18 @@ def test_to_frame(self):
         df = idx.to_frame(index=False)
         assert df.index is not idx
 
+        # See GH-22580
+        new_idx_name = 'new_name'
+        df = idx.to_frame(name=new_idx_name)
+
+        assert df.index is idx
+        assert len(df.columns) == 1
+        assert df.columns[0] == new_idx_name
+        assert df[new_idx_name].values is not idx.values
+
+        df = idx.to_frame(index=False, name=new_idx_name)
+        assert df.index is not idx
+
     def test_shift(self):
 
         # GH8083 test the base class for shift

pandas/tests/indexes/multi/test_conversion.py

@@ -37,6 +37,27 @@ def test_to_frame():
     expected.index = index
     tm.assert_frame_equal(result, expected)
 
+    # See GH-22580
+    index = MultiIndex.from_tuples(tuples)
+    result = index.to_frame(index=False, name=['first', 'second'])
+    expected = DataFrame(tuples)
+    expected.columns = ['first', 'second']
+    tm.assert_frame_equal(result, expected)
+
+    result = index.to_frame(name=['first', 'second'])
+    expected.index = index
+    expected.columns = ['first', 'second']
+    tm.assert_frame_equal(result, expected)
+
+    msg = "'name' must be a list / sequence of array-likes."
+    with tm.assert_raises_regex(TypeError, msg):
+        index.to_frame(name='first')
+
+    msg = "'name' should have same length as number of levels on index"
+    with tm.assert_raises_regex(ValueError, msg):
+        index.to_frame(name=['first'])
+
+    # Tests for datetime index
     index = MultiIndex.from_product([range(5),
                                      pd.date_range('20130101', periods=3)])
     result = index.to_frame(index=False)
@@ -45,12 +66,21 @@ def test_to_frame():
             1: np.tile(pd.date_range('20130101', periods=3), 5)})
     tm.assert_frame_equal(result, expected)
 
-    index = MultiIndex.from_product([range(5),
-                                     pd.date_range('20130101', periods=3)])
     result = index.to_frame()
     expected.index = index
     tm.assert_frame_equal(result, expected)
 
+    # See GH-22580
+    result = index.to_frame(index=False, name=['first', 'second'])
+    expected = DataFrame(
+        {'first': np.repeat(np.arange(5, dtype='int64'), 3),
+         'second': np.tile(pd.date_range('20130101', periods=3), 5)})
+    tm.assert_frame_equal(result, expected)
+
+    result = index.to_frame(name=['first', 'second'])
+    expected.index = index
+    tm.assert_frame_equal(result, expected)
+
 
 def test_to_hierarchical():
     index = MultiIndex.from_tuples([(1, 'one'), (1, 'two'), (2, 'one'), (