Groupby and sum columns in python(default functionalities, Pandas and ittertools)

groupby_sum_fields_in_python_default _and_pandas_ittertools.py

# -*- coding: utf-8 -*-

# Default Method

# Get Unique product details => group by reapit_product_id and sum by quantity
grpby_key = 'product_id'
sum_key = 'qty'

data = [
    {'product_id': 1, 'desc': 'Desc1', 'qty': 2, 'unit_price': 2, 'total': 4},
    {'product_id': 1, 'desc': 'Desc1', 'qty': 3, 'unit_price': 2, 'total': 6},
    {'product_id': 1, 'desc': 'Desc1', 'qty': 3, 'unit_price': 2, 'total': 6},
    {'product_id': 2, 'desc': 'Desc2', 'qty': 2, 'unit_price': 5, 'total': 10},
    {'product_id': 3, 'desc': 'Desc3', 'qty': 3, 'unit_price': 7, 'total': 21},
    {'product_id': 1, 'desc': 'Desc1', 'qty': 3, 'unit_price': 2, 'total': 6},
]

def grpby_sum_list_dict(list_data, groupby_key, sum_key):
    new_data = []
    for p in {x.get(groupby_key) for x in list_data}:
        val = {}
        qty = sum([x.get(sum_key) for x in list_data if x[groupby_key] == p])
        for i in list_data:
            if i.get(groupby_key) == p:
                val = i
            val[sum_key] = qty
        new_data.append(val)
    return new_data
print(grpby_sum_list_dict(data, grpby_key, sum_key))

fdata = []

print "Original Data : ", data

# Group by and sum Using Pandas
import pandas as pd

df = pd.DataFrame(data)  # Dict to Data frame

product_id = df.groupby(gby_field)  # Grouped dataframe


p_sum = product_id.sum()  # sum all the float fields based on groupby field


fdict = p_sum.to_dict()  # Convert dataframe to Dict

gby_field_data = list(set([x.get(gby_field) for x in data]))  # To get uniuqe product_data


gby_field_desc_data = {x.get(gby_field): x.get('desc') for x in data}  # To get Unique product desc(String Fields)


for gby in gby_field_data:
    fdata.append({'product_id': gby, 'qty': fdict['qty'][gby], 'desc': gby_field_desc_data[gby], 'unit_price': fdict['unit_price'][gby], 'total': fdict['total'][gby]})

print("Results From Pandas: ", fdata)

# Group by and sum Using ittertools
import itertools
from operator import itemgetter

fdata = []

sorted_data = sorted(data, key=itemgetter(gby_field))  # Sort the data
group_dict = itertools.groupby(sorted_data, key=lambda x: x[gby_field])  # group the content data
for key, group in group_dict:
    key_data = list(group)
    field_data = {gby_field: key}
    for x in key_data:
        for k, v in x.items():
            if k != gby_field:
                if k in field_data:
                    field_data[k] += v
                else:
                    field_data.update({k: v})
    fdata.append(field_data)

print("Results From ItterTools: ", fdata)


# Output:

# ('Results From Pandas: ', [{'total': 22, 'desc': 'Desc1', 'product_id': 1, 'unit_price': 8, 'qty': 11}, {'total': 10, 'desc': 'Desc2', 'product_id': 2, 'unit_price': 5, 'qty': 2}, {'total': 21, 'desc': 'Desc3', 'product_id': 3, 'unit_price': 7, 'qty': 3}])
# ('Results From ItterTools: ', [{'desc': 'Desc1Desc1Desc1Desc1', 'total': 22, 'product_id': 1, 'unit_price': 8, 'qty': 11}, {'desc': 'Desc2', 'total': 10, 'product_id': 2, 'unit_price': 5, 'qty': 2}, {'desc': 'Desc3', 'total': 21, 'product_id': 3, 'unit_price': 7, 'qty': 3}])