Merge resets column types - category is reset
#### Code Sample, a copy-pastable example if possible

```
import numpy as np
import pandas as pd
# Generate some random dataframes with a common "id" column to merge on
# Transform some columns into type "category"
some_strings = ['aa', 'bb', 'cc', 'dd']
d1 = {'id': np.arange(100),
      'var1': np.random.randint(0,10,size=100),
      'var2': np.random.uniform(size=100),
      'var3': np.random.randint(0,2,size=100),
      'var4': np.random.choice(some_strings, 100)}
df1 = pd.DataFrame(d1)
df1['var1'] = df1['var1'].astype('category')

d2 = {'id': np.arange(100),
      'var1': np.random.randint(0,10,size=100),
      'var2': np.random.uniform(size=100),
      'var3': np.random.randint(0,2,size=100),
      'var4': np.random.choice(some_strings, 100)}
df2 = pd.DataFrame(d2)
df2['var1'] = df2['var1'].astype('category')
df2['var4'] = df2['var4'].astype('category')

print 'df1'
print df1.info() #Shows categorical columns

print 'df2'
print df2.info() #Shows categorical columns
print pd.merge(df1, df2, on='id').info() #Categorical columns are no longer categorical
```
#### Expected Output

The merged df1 and df2 no longer has category columns, and are reset to their original types.
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Linux
OS-release: 2.6.32-431.23.3.el6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.17.1
nose: 1.3.7
pip: 7.1.2
setuptools: 18.5
Cython: 0.23.4
numpy: 1.10.1
scipy: 0.16.0
statsmodels: 0.6.1
IPython: 4.0.1
sphinx: 1.3.1
patsy: 0.4.0
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.4.4
matplotlib: 1.5.0
openpyxl: 2.2.6
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.7.7
lxml: 3.4.4
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.9
pymysql: None
psycopg2: None
Jinja2: None
