Pandas dataframe eval 
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
Scenario 1:

df2=pd.DataFrame({'a1':[10,20]})

df2.eval("c=((a1>10) & True )")
Out[8]: 
   a1      c
0  10  False
1  20   True
Scenario 2:
df2=pd.DataFrame({'a1':['Y','N']})
df2.eval("c=((a1 == 'Y') & True )")
Traceback (most recent call last):

TypeError: issubclass() arg 1 must be a class






```
#### Problem description

[this should explain **why** the current behaviour is a problem and why the expected output is a better solution.]
By changing datatype of a column from int to str, pd.eval throws "TypeError: issubclass() arg 1 must be a class" 


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https://pandas-docs.github.io/pandas-docs-travis/

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#### Expected Output
In Scenario 2

 a1      c
  10  True
 20   False

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: None.None

pandas: 0.21.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.14.2
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None


</details>
