ENH: convert datetime components (year, month, day, ...) in different columns to datetime
from [SO](http://stackoverflow.com/questions/36804141/vectorized-construction-of-datetimeindex-in-pandas)

I didn't find an issue about this, but it has come up some times at stackoverflow: having columns with integers for year, month, day, hour, ..., how do you convert this to a datetime column/index ?

http://stackoverflow.com/questions/19350806/how-to-convert-columns-into-one-datetime-column-in-pandas

You have the typical solution of adding the columns: `pd.to_datetime((df['Y']*10000 + df['M']*100 + df['D']).astype('int'), format='%Y%m%d')`, and @unutbu added now a faster solution using numpy's different datetime64 resolutions to that question on SO.

I personally think this would be a nice addition to pandas to have a more native solution for this. But then we need to figure out a nice API. Or we keep it as is, but try to document it more (add as example to docs?)
