Grouping daily data by month in python/pandas and then normalising

Grouping daily data by month in python/pandas and then normalising

Hi I have the table bellow in a Pandas dataframe:
q_string q_visits q_date
0 nucleus 1790 2012-10-02 00:00:00
1 neuron 364 2012-10-02 00:00:00
2 current 280 2012-10-02 00:00:00
3 molecular 259 2012-10-02 00:00:00
4 stem 201 2012-10-02 00:00:00
The table contains query volume from a server log, by day. I would like to
do 2 things:
(1) I would like to group queries by month summing the query volume of a
query for the whole month e.g. if 'molecular' was present on the
2012-10-02 with volume 1000 and on the 2012-10-03 with volume 500, then it
should have an entry in the new table of 1500 (volume) with date
2012-10-31 (end of the month end-point representing the month - all dates
in the transformed table will be month ends representing the whole month
to which they relate).
(2) I want to add a 5th column which contains the month-normalised
'q_visits' i.e. a term's monthly query volume divided by the total query
volume for the month across all terms.
What is the best way of doing this?
Thanks in advance for any help.