Feature suggestion: use ciso8601 in pd.to_datetime for great speed
**tl;dr** [ciso8601](https://github.com/closeio/ciso8601) is a module that's over 450x faster than pandas.to_datetime for data in ISO8601 format

#### Problem description

pd.to_datetime is robust to various formats and works nice.

I was trying to convert a series of 3.5 million timestamps into python objects, and it was taking long enough for me to start looking for alternatives. Found **[this.](https://www.peterbe.com/plog/fastest-python-datetime-parser)**

Result:
<img width="726" alt="screen shot 2018-06-28 at 9 31 05 pm" src="https://user-images.githubusercontent.com/7082264/42060047-69304f1c-7b1d-11e8-8792-164ce926cdac.png">


I'm on the 2017 macbook pro, pandas was using one core.  
I tried on 100k observations as well - 12s pandas vs 43ms ciso  (280x)
Your mileage may vary, but it's safe to say the improvement is significant enough for bigger datasets.

Does it make sense to try and take advantage of this nice treat? If yes, how to go about it?

Thanks
