Merge on categorical type columns gives wrong results
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
from pandas.api.types import CategoricalDtype

# Setup CategoricalDtype causing issue
cat_type1 = CategoricalDtype(categories=['A', 'B', 'C'], ordered=False)
cat_type2 = CategoricalDtype(categories=['C', 'B', 'A'], ordered=False)

print('Check dtypes are equivalent:', cat_type1 == cat_type2)
print()

# Test Data
df1 = pd.DataFrame({
    'Foo': pd.Series(['A', 'B', 'C']).astype(cat_type1),
    'Left': ['A0', 'B0', 'C0'],
})

df2 = pd.DataFrame({
    'Foo': pd.Series(['C', 'B', 'A']).astype(cat_type2),
    'Right': ['C1', 'B1', 'A1'],
})

print('df1:\n', df1)
print()

print('df2:\n', df2)
print()

# Issue happens here. Merges on codes instead of value.
# Notice, data from df2 isn't merged correctly.
df_merge = df1.merge(df2, on=['Foo'])
print('df_merge:\n', df_merge)
print()

results = """
Check dtypes are equivalent: True

df1:
   Foo Left
0   A   A0
1   B   B0
2   C   C0

df2:
   Foo Right
0   C    C1
1   B    B1
2   A    A1

df_merge:
   Foo Left Right
0   A   A0    C1
1   B   B0    B1
2   C   C0    A1
"""

```
#### Problem description

Since upgrading from `v0.20.3` to `v0.22.0` I noticed data missing on my datasets. After a few hours debugging I narrowed it down to an issue involving **merges that involve `Categoricals`**. I downgraded to `v0.20.3` to test my original code and didn't have the issue. I then tested on `v.0.21.0` and noticed the issue was first introduced on that version. 

While the example provided doesn't run in `v0.20.3`, it does highlight the bug and I think shows why its happening. Notice that the merge should give a result of 

```
   Foo Left Right
0   A   A0    A1
1   B   B0    B1
2   C   C0    C1
```

instead of 

```
   Foo Left Right
0   A   A0    C1  # Wrong
1   B   B0    B1
2   C   C0    A1  # Wrong
```

#### Expected Output
```
   Foo Left Right
0   A   A0    A1
1   B   B0    B1
2   C   C0    C1
```

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 79 Stepping 1, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.5.0.post20170921
Cython: 0.26.1
numpy: 1.12.1
scipy: 0.19.1
pyarrow: 0.7.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.0
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
