RecursionError when using pd.eval with numexpr on all None object series
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

df = pd.DataFrame({'a': [None, None]})

df.eval('a + a', engine='python')
"""
>>> df.eval('a + a', engine='python')
0    NaN
1    NaN
Name: a, dtype: object
"""

# Results in RecursionError
df.eval('a + a', engine='numexpr')
```
#### Problem description
Evaluation of the expression should be consistent between python engine and numexpr engine.  I assume the python engine behavior would be the preferred behavior.

#### Expected Output
>>> df.eval('a + a', engine='numexpr')
0    NaN
1    NaN
Name: a, dtype: object

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-143-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.0
pytest: None
pip: 9.0.1
setuptools: 36.4.0
Cython: None
numpy: 1.13.1
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.5
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
