BUG: assignment with .at or .loc modifies dataframe when it fails
#### Code Sample, a copy-pastable example if possible

```
d = pd.DataFrame()
try:
   d.set_value(0, "c", [1,2,4]) 
except Exception:
  print "Caught"

print d  # c is now in d 

```
#### Problem description

The above call set_value (correctly) fails and throw an exception. However, the dataframe has been modified. It has a new 'c' column of type float. Because the operation failed, it probably should have remained unchanged.

#### Expected Output

print d should print an empty dataframe.

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Linux
OS-release: 4.2.0-41-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.19.1
nose: 1.3.1
pip: 1.5.4
setuptools: 3.3
Cython: 0.25.1
numpy: 1.11.2
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 4.2.1
sphinx: None
patsy: 0.2.1
dateutil: 2.6.0
pytz: 2016.7
blosc: None
bottleneck: None
tables: 3.1.1
numexpr: 2.2.2
matplotlib: 1.3.1
openpyxl: 1.7.0
xlrd: 0.9.2
xlwt: 0.7.5
xlsxwriter: None
lxml: None
bs4: 4.2.1
html5lib: 0.999
httplib2: 0.8
apiclient: None
sqlalchemy: 1.0.15
pymysql: None
psycopg2: 2.4.5 (dt dec mx pq3 ext)
jinja2: 2.8
boto: 2.41.0
pandas_datareader: None
</details>
