pd.to_numeric - float64, object or error?
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

print pd.__version__

#different result example
d = pd.DataFrame({'a':[200, 300, '', 'NaN', 10000000000000000000]})

#returns dtype object
a = pd.to_numeric(d['a'], errors='coerce')
print a.dtype

#return dtype float64
b = d['a'].apply(pd.to_numeric, errors='coerce')
print b.dtype

#why not float64?
d = pd.DataFrame({'a':[200, 300, '', 'NaN', 30000000000000000000]})

#returns dtype object
a = pd.to_numeric(d['a'], errors='coerce')
print a.dtype

#returns OverflowError
b = d['a'].apply(pd.to_numeric, errors='coerce')
print b.dtype
```
#### Problem description

Hi guys, I realized that result of to_numeric changes depending on the way you pass a Series to that function. Please see example above. When I call to_numeric with series passed as parameter, it returns "object", but when I apply to_numeric to that series, it returns "float64". Moreover, I'm a bit confused what's the correct behavior of to_numeric, why it doesn't convert looooong int-like number to float64? It throws an exception from which I can't even deduce which number (position, index) caused that exception... 

I'm pretty sure my issue is being discussed somewhere already, I tried to search the proper issue but rather found bits and pieces about to_numeric and convertions in general. Please feel free to put my issue in more appropriate thread. 

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

<details>
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 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 27.2.0
Cython: None
numpy: 1.13.1
scipy: None
xarray: None
IPython: 5.4.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
