BUG: fix DataFrame constructor w named Series

doc/source/whatsnew/v0.16.0.txt

@@ -367,6 +367,13 @@ The behavior of a small sub-set of edge cases for using ``.loc`` have changed (:
  In [4]: df.loc[2:3]
  TypeError: Cannot do slice indexing on <class 'pandas.tseries.index.DatetimeIndex'> with <type 'int'> keys
 
+DataFrame Construction Changes
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. _whatsnew_0160.api_breaking.construction:
+
+
+
 
 .. _whatsnew_0160.deprecations:
 
@@ -535,3 +542,7 @@ Bug Fixes
 - Fixed bug with reading CSV files from Amazon S3 on python 3 raising a TypeError (:issue:`9452`)
 
 - Bug in the Google BigQuery reader where the 'jobComplete' key may be present but False in the query results (:issue:`8728`)
+
+
+- Fixed bug with DataFrame constructor when passed a Series with a
+name and the `columns` keyword argument.

pandas/core/frame.py

@@ -231,7 +231,7 @@ def __init__(self, data=None, index=None, columns=None, dtype=None,
  if columns is None:
  columns = data_columns
  mgr = self._init_dict(data, index, columns, dtype=dtype)
- elif getattr(data, 'name', None):
+ elif getattr(data, 'name', None) is not None:
  mgr = self._init_dict({data.name: data}, index, columns,
  dtype=dtype)
  else:
@@ -295,16 +295,15 @@ def _init_dict(self, data, index, columns, dtype=None):
  if columns is not None:
  columns = _ensure_index(columns)
 
- # prefilter if columns passed
-
- data = dict((k, v) for k, v in compat.iteritems(data)
- if k in columns)
-
  if index is None:
  index = extract_index(list(data.values()))
  else:
  index = _ensure_index(index)
 
+ # prefilter if columns passed
+ data = dict((k, v) for k, v in compat.iteritems(data)
+ if k in columns)
+
  arrays = []
  data_names = []
  for k in columns:

pandas/tests/test_frame.py

@@ -3362,6 +3362,18 @@ def test_constructor_Series_named(self):
  expected = DataFrame({ 1 : s1, 0 : arr },columns=[0,1])
  assert_frame_equal(df,expected)
 
+ def test_constructor_Series_named_different(self):
+ # 9232
+ x = Series([1, 2], name=0)
+ expected = DataFrame([np.nan, np.nan], columns=[1])
+ result = DataFrame(x, columns=[1])
+ assert_frame_equal(result, expected)
+
+ x.name = 1
+ expected = DataFrame([np.nan, np.nan], columns=[0])
+ result = DataFrame(x, columns=[0])
+ assert_frame_equal(result, expected)
+
  def test_constructor_Series_differently_indexed(self):
  # name
  s1 = Series([1, 2, 3], index=['a', 'b', 'c'], name='x')