df[column].dtype in {int, float} does not evaluate correctly
Comparing dtypes of DataFrame columns works fine for a list of possible dtypes, but not for a set of possible dtypes. For example:

``` python
In [1]: sample_df = pd.DataFrame(
            [[1,2,3],[4,5,6],[7,8,9],[10,11,12]], 
            columns=['a', 'b', 'c']
        )

In [2]: sample_df.dtypes
Out[2]: 
a    int64
b    int64
c    int64
dtype: object

In [3]: [sample_df[c].dtype in [int] for c in sample_df.columns]
Out[3]: [True, True, True]

In [4]: [sample_df[c].dtype in {int} for c in sample_df.columns]
Out[4]: [False, False, False]
```

What is the cause of this behaviour? I would expect `[sample_df[c].dtype in {int} for c in sample_df.columns]` to evaluate to `[True, True, True]` as well. 

I am using pandas version 0.15.0.

``` python
pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-43-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_CA.UTF-8

pandas: 0.15.0
nose: 1.3.4
Cython: 0.21
numpy: 1.9.1
scipy: 0.14.0
statsmodels: 0.5.0
IPython: 2.3.1
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 1.5
pytz: 2014.9
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.2
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: None
httplib2: 0.9
apiclient: None
rpy2: 2.4.2
sqlalchemy: 0.8.2
pymysql: None
psycopg2: 2.5.3 (dt dec pq3 ext)
```
