BUG: crosstab cannot normalize multiple columns for the index
#### Code Sample, a copy-pastable example if possible

```python
df = pd.DataFrame({'A': ['one', 'one', 'two', 'three'] * 6, 'B': ['A', 'B', 'C'] * 8, 'C' : ['foo', 'foo', 'foo', 'bar', 'bar', 'bar'] * 4, 'D': np.random.randn(24), 'E': np.random.randn(24)})

pd.crosstab([df.A, df.B], df.C, values=df.D, aggfunc=np.sum, normalize=True, margins=True)

```
#### Problem description

This gives "ValueError: labels ['All'] not contained in axis"

Currently, crosstab only normalize single index.
I expect crosstab can normalize with multiple columns for the index, but I got ValueError: labels ['All'] not contained in axis. 

#### Expected Output
normalized result

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

<details>
# Paste the output here pd.show_versions() here

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-47-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: None
pip: 9.0.1
setuptools: 28.8.0
Cython: None
numpy: 1.11.2
scipy: 0.18.1
statsmodels: None
xarray: None
IPython: 5.1.0
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2016.7
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.1.4
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None
None

</details>
