Aggregating and calculating in Ordereddict in Python

Question

Have a Ordereddict "d" looking like that:

[OrderedDict([
              ('id', '1'),
              ('date', '20170101'),
              ('quantity', '10')]),
 OrderedDict([
              ('id', '2'),
              ('date', '20170102'),
              ('quantity', '3')]),
 OrderedDict([
              ('id', '3'),
              ('date', '20170102'),
              ('quantity', '1')])]

I'm trying to do the group by 'date' and calculating the sum of quantity and display these two columns 'date' and 'sum_quantity'. How can I do that not using pandas groupby options?

Thanks!

Answer 1

Here is pure python approach, This is just an example to give you a hint. If you want in pure python you can use this.

from collections import OrderedDict
import itertools
data=[OrderedDict([
              ('id', '1'),
              ('date', '20170101'),
              ('quantity', '10')]),
 OrderedDict([
              ('id', '2'),
              ('date', '20170102'),
              ('quantity', '3')]),
 OrderedDict([
              ('id', '3'),
              ('date', '20170102'),
              ('quantity', '1')])]



def get_quantity(ord_dict):
    new_ = []
    for g in [list(i) for j, i in itertools.groupby(ord_dict, lambda x: x['date'])]:
        if len(g) > 1:
            sub_dict={}
            temp = []
            date = []
            for i in g:
                temp.append(int(i['quantity']))
                date.append(i['date'])
            sub_dict['date'] = date[0]
            sub_dict['sum_quantity'] = sum(temp)
            new_.append(sub_dict)


        else:
            for i in g:
                sub_dict={}
                sub_dict['date']=i['date']
                sub_dict['sum_quantity']=i['quantity']
                new_.append(sub_dict)

    return new_
print(get_quantity(data))

output:

[{'date': '20170101', 'sum_quantity': '10'}, {'date': '20170102', 'sum_quantity': 4}]