value_counts failed on unique list values
#### When value_counts on different list value, it's ok:

```python
ser1 = pd.Series([[1], [2], [2]])
ser1.value_counts()

[2]    2
[1]    1
dtype: int64
```

#### But, when value_counts on unique list value, it's failed:
```python
ser2 = pd.Series([[1], [1], [1]])
ser2.value_counts()

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-64-845402fb8b57> in <module>()
      1 ser2 = pd.Series([[1], [1], [1]])
----> 2 ser2.value_counts()

/home/centos/anaconda2/lib/python2.7/site-packages/pandas/core/base.pyc in value_counts(self, normalize, sort, ascending, bins, dropna)
    945         from pandas.core.algorithms import value_counts
    946         result = value_counts(self, sort=sort, ascending=ascending,
--> 947                               normalize=normalize, bins=bins, dropna=dropna)
    948         return result
    949 

/home/centos/anaconda2/lib/python2.7/site-packages/pandas/core/algorithms.pyc in value_counts(values, sort, ascending, normalize, bins, dropna)
    276     else:
    277         # ndarray path. pass original to handle DatetimeTzBlock
--> 278         keys, counts = _value_counts_arraylike(values, dropna=dropna)
    279 
    280         from pandas import Index, Series

/home/centos/anaconda2/lib/python2.7/site-packages/pandas/core/algorithms.pyc in _value_counts_arraylike(values, dropna)
    346         values = com._ensure_object(values)
    347         mask = com.isnull(values)
--> 348         keys, counts = htable.value_count_object(values, mask)
    349         if not dropna and mask.any():
    350             keys = np.insert(keys, 0, np.NaN)

pandas/hashtable.pyx in pandas.hashtable.value_count_object (pandas/hashtable.c:18970)()

pandas/hashtable.pyx in pandas.hashtable.value_count_object (pandas/hashtable.c:18705)()

TypeError: unhashable type: 'list'
```

#### I tried 1.18.1 and 1.19.0

#### Output of ``pd.show_versions()``, 1.18.1
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-327.36.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 27.2.0
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: None

#### Output of ``pd.show_versions()``, 1.19.0

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-45-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.19.0
nose: 1.3.7
pip: 8.1.2
setuptools: 27.2.0
Cython: 0.24.1
numpy: 1.11.2
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.7
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: None
