Pandas doesn't recognize Pyarrow as a Parquet engine even though it's installed
#### Code Sample, a copy-pastable example if possible

```python
In [6]: pd.io.parquet.get_engine('auto')
---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-6-77cb1d6c8933> in <module>
----> 1 pd.io.parquet.get_engine('auto')

~/miniconda3/lib/python3.6/site-packages/pandas/io/parquet.py in get_engine(engine)
     30             pass
     31
---> 32         raise ImportError("Unable to find a usable engine; "
     33                           "tried using: 'pyarrow', 'fastparquet'.\n"
     34                           "pyarrow or fastparquet is required for parquet "

ImportError: Unable to find a usable engine; tried using: 'pyarrow', 'fastparquet'.
pyarrow or fastparquet is required for parquet support
```
#### Problem description

Pandas doesn't recognize Pyarrow as a Parquet engine even though it's installed. Note that you can see that Pyarrow 0.12.0 is installed in the output of `pd.show_versions()` below. 

#### Expected Output

```
In [2]: pd.io.parquet.get_engine('auto')
Out[2]: <pandas.io.parquet.PyArrowImpl at 0x119c78f28>
```

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

<details>
In [5]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-29-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.0
pytest: 3.9.3
pip: 18.1
setuptools: 40.5.0
Cython: None
numpy: 1.15.4
scipy: 1.1.0
pyarrow: 0.12.0
xarray: None
IPython: 7.1.1
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: 4.2.5
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
</details>
