ENH: allow index of col names in set_index GH10797

doc/source/whatsnew/v0.18.0.txt

@@ -110,6 +110,7 @@ Other enhancements
 - ``DataFrame`` has gained a ``_repr_latex_`` method in order to allow for automatic conversion to latex in a ipython/jupyter notebook using nbconvert. Options ``display.latex.escape`` and ``display.latex.longtable`` have been added to the configuration and are used automatically by the ``to_latex`` method. (:issue:`11778`)
 - ``sys.getsizeof(obj)`` returns the memory usage of a pandas object, including the
   values it contains (:issue:`11597`)
+- ``set_index`` now interprets views of the columns index passed to the keys parameter as lists of existing columns to use as the index (:issue:`10797`)
 
 .. _whatsnew_0180.enhancements.rounding:
 

pandas/core/frame.py

@@ -2727,11 +2727,16 @@ def set_index(self, keys, drop=True, append=False, inplace=False,
                   verify_integrity=False):
         """
         Set the DataFrame index (row labels) using one or more existing
-        columns. By default yields a new object.
+        columns and/or new arrays of values. By default yields a new object.
 
         Parameters
         ----------
-        keys : column label or list of column labels / arrays
+        keys : column label (str), Index, Series, array, or a list of these things
+            Existing columns to set as the index (when given columns labels)
+            and/or new values to set as new index values. If an Index is given,
+            it will be used as a new index unless it is a view of the column
+            index, in which case it will be interpreted as a set of existing
+            columns to set as the index.
         drop : boolean, default True
             Delete columns to be used as the new index
         append : boolean, default False
@@ -2748,13 +2753,26 @@ def set_index(self, keys, drop=True, append=False, inplace=False,
         >>> indexed_df = df.set_index(['A', 'B'])
         >>> indexed_df2 = df.set_index(['A', [0, 1, 2, 0, 1, 2]])
         >>> indexed_df3 = df.set_index([[0, 1, 2, 0, 1, 2]])
+        >>> indexed_df4 = df.set_index(df.columns[:2])
 
         Returns
         -------
         dataframe : DataFrame
         """
         if not isinstance(keys, list):
-            keys = [keys]
+            if isinstance(keys, Index):
+                # if the index is a slice of the column index, treat it like
+                # a list of column labels; otherwise, treat it like a new index
+                keys_base = keys.base
+                while isinstance(keys_base, Index):
+                    keys_base = keys_base.base
+                cols_base = self.columns.base
+                while isinstance(cols_base, Index):
+                    cols_base = cols_base.base
+                if keys_base is not cols_base:
+                    keys = [keys]
+            else:
+                keys = [keys]
 
         if inplace:
             frame = self

pandas/tests/test_frame.py

@@ -2583,6 +2583,42 @@ def test_set_index_empty_column(self):
         result = df.set_index(['a', 'x'])
         repr(result)
 
+    def test_set_index_with_index(self):
+        # GH10797: It should be possible to use a slice of the column index as
+        # the `keys` parameter in set_index().
+
+        # Test that setting the first two columns as the index can be done
+        # either with a list of column labels or a slice of the column index.
+        df = DataFrame({'col1': [1, 2, 3, 4, 5, 6],
+                        'col2': ['a', 'b', 'c', 'a', 'b', 'c'],
+                        'col3': [0.0, 0.0, 1.0, 1.0, 2.0, 2.0]})
+        expected_index = MultiIndex(levels=[['a', 'b', 'c'], [0.0, 1.0, 2.0]],
+                                    labels=[[0, 1, 2, 0, 1, 2],
+                                            [0, 0, 1, 1, 2, 2]],
+                                    names=['col2', 'col3'])
+        expected_df = DataFrame(data={'col1': [1, 2, 3, 4, 5, 6]},
+                                index=expected_index)
+        list_df = df.set_index(['col2', 'col3'])
+        assert_frame_equal(expected_df, list_df)
+        index_df = df.set_index(df.columns[1:])
+        assert_frame_equal(expected_df, index_df)
+
+        # Test that passing the entire index results in an empty dataframe (i.e.
+        # all columns become part of the index).
+        empty_df = df.set_index(df.columns)
+        assert_equal(len(empty_df.columns), 0)
+        assert_equal(empty_df.index.nlevels, 3)
+
+        # Test that an index that is created independently of the column index
+        # is used as a new index - not as a set of column labels.
+        new_index = Index(data=['col1', 'col1', 'col2', 'col2', 'col3', 'col3'])
+        expected_df2 = DataFrame({'col1': [1, 2, 3, 4, 5, 6],
+                        'col2': ['a', 'b', 'c', 'a', 'b', 'c'],
+                        'col3': [0.0, 0.0, 1.0, 1.0, 2.0, 2.0]},
+                                index=new_index)
+        col_name_index_df = df.set_index(new_index)
+        assert_frame_equal(expected_df2, col_name_index_df)
+
     def test_set_columns(self):
         cols = Index(np.arange(len(self.mixed_frame.columns)))
         self.mixed_frame.columns = cols