mongodb pymongo collection group by example.py

mongodb collection group by example

            start_date = str(get_format_date(begin_timestamp))
            end_date = str(get_format_date(end_timestamp))

            match = {
                'date': {
                    '$gte': start_date,
                    '$lte': end_date,
                }
            }

            groupby = ['account_name', 'region']

            group = {
                '_id': {key: ('$%s' % key) for key in groupby} or {'None': '$None'},
                'fee': {'$sum': '$fee'},
                'cost': {'$sum': '$cost'},
                'system_size': {'$sum': '$system_size'},
                'user_size': {'$sum': '$user_size'},
            }

            rets = db.gddata_daily_stats.aggregate(
                [
                    {'$match': match},
                    {'$group': group},
                ]
            )

            for ret in rets['result']:
                account_period = {
                    'account_name': ret['_id']['account_name'],
                    'region': ret['_id']['region'],
                    'fee': ret['fee'],
                    'cost': ret['cost'],
                    'system_size': ret['system_size'],
                    'user_size': ret['user_size'],
                }
                account_period_lists.append(account_period)
            new_account_data_bill_dataframe = pandas.DataFrame(account_period_lists,
                                                               columns=['account_name', 'region', 'fee', 'cost',
                                                                        'system_size', 'user_size'])