Support creating a DataFrame from a list of dictionaries providing an index column
Hey Wes,

Here's a use case that I think is not covered by Pandas.
It's a use case for creation of a DataFrame object from a
list of dicts.

I extract "documents" (dicts) from a MongoDB database.
From these dicts, one of the keys is meant to be used as 
the index.

While I can do something like

  df = DataFrame(documents, columns=['order_id', 'time', 'quantity'])

the index that is added is an arbitrary one.
I'd like to use 'order_id' as my index, in this example.
The only way for me to do that at the moment is to create
the index explicitly, e.g. like this:

  df = DataFrame(documents, columns=['order_id', 'time', 'quantity'],
                 index=[o['order_id'] for o in documents])

This is a bit of a PIA. It would be nice if one could just
specify the index key/column name, e.g.

  df = DataFrame(documents, columns=['order_id', 'time', 'quantity'], indexcol='order_id')

That's my use case almost everywhere.
