view into modified dataframe of ints causes subsequent set_value to not work properly
The following code snippet produces unexpected output:

``` python
import pandas as pd
import numpy as np
x = pd.DataFrame(data=np.zeros((5,5),dtype=np.int),columns=['a','b','c','d','e'])
x['f'] = 0
x.f.values[3]=1
y = x.iloc[np.arange(2,len(x))]
x.f.values[3]=2
print x
print x.f.values
```

```
Out[130]: 
   a  b  c  d  e  f
0  0  0  0  0  0  0
1  0  0  0  0  0  0
2  0  0  0  0  0  0
3  0  0  0  0  0  1
4  0  0  0  0  0  0
[0 0 0 2 0]
```

The expected output is:

```
Out[131]: 
   a  b  c  d  e  f
0  0  0  0  0  0  0
1  0  0  0  0  0  0
2  0  0  0  0  0  0
3  0  0  0  0  0  2
4  0  0  0  0  0  0
[0 0 0 2 0]
```

The behavior only manifests if the dataframe has had a column added to it (f in this case), if the columns are ints, and if the view is constructed with certain kinds of indexing (y=x.iloc[2:] works fine for instance).

Here is my version info:
## INSTALLED VERSIONS

commit: None
python: 2.7.7.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-229.4.2.el7.jump.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.15.2.dev
nose: 1.3.4
Cython: 0.20.2
numpy: 1.9.0
scipy: 0.14.1rc1.dev-Unknown
statsmodels: None
IPython: 3.1.0
sphinx: 1.3b1
patsy: 0.3.0
dateutil: 2.2
pytz: 2014.10
bottleneck: 0.8.0
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.0
openpyxl: 2.1.4
xlrd: None
xlwt: None
xlsxwriter: None
lxml: 3.4.2
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
rpy2: 2.4.3
sqlalchemy: None
pymysql: 0.6.2.None
psycopg2: 2.5.4 (dt dec pq3 ext)
