columns= specification when constructing dataframe from named Series now selects instead of renaming columns
In pandas 0.12 and previous, I could construct a new DataFrame from a Series and use the "columns=" specifier to set the column name. This is particularly efficient to use when creating new DataFrames from groupby aggregations without requiring a second step of renaming the columns in the new DataFrame. It seems that in pandas 0.13.1 this has changed behavior to instead only select those columns from the source data/Series. 

In 0.12

``` python
In [9]: S = Series([1,2,3],name='blah')

In [10]: DataFrame(S, columns=['asdf'])
Out[10]: 
   asdf
0     1
1     2
2     3
```

But in 0.13.1 this behavior has changed:

``` python
In [4]: S = Series([1,2,3],name='blah')

In [5]: DataFrame(S, columns=['asdf'])
Out[5]: 
Empty DataFrame
Columns: [asdf]
Index: []

[0 rows x 1 columns]

```

the applicable versions for 0.13.1 are:

``` python
In [7]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Darwin
OS-release: 13.0.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.13.1
Cython: 0.19.2
numpy: 1.8.0
scipy: 0.13.0
statsmodels: 0.5.0
IPython: 1.2.0
sphinx: 1.1.3
patsy: 0.2.1
scikits.timeseries: None
dateutil: 2.2
pytz: 2013.9
bottleneck: None
tables: 3.0.0
numexpr: 2.2.2
matplotlib: 1.3.1
openpyxl: 1.6.2
xlrd: 0.9.2
xlwt: 0.7.5
xlsxwriter: None
sqlalchemy: 0.8.3
lxml: 3.2.3
bs4: 4.3.1
html5lib: None
bq: None
apiclient: 1.2
```
