Keeney apply

k.py

from pprint import pprint
from collections import defaultdict

import pandas as pd

data = [
    {'item_code': "A1234", "contract_size": 1, "contract_number": 1},
    {'item_code': "B1234", "contract_size": 3, "contract_number": 1},
    {'item_code': "01234", "contract_size": 1, "contract_number": 2},
    {'item_code': "X1234", "contract_size": 2, "contract_number": 2},
]

contract_values = {}
for row in data:
    cn = row['contract_number']
    if cn not in contract_values:
        contract_values[cn] = 0
    contract_values[cn] += row['contract_size']


def sorter(item_code: str):
    code = item_code[0].upper()
    if code in '1234567890':
        return 'comm'
    if code in 'XY':
        return 'service'
    return 'keeney'

def contract_size(contract: int):
    return contract_values[contract]


df = pd.DataFrame(data)
df['something'] = df['item_code'].apply(sorter)
df['total_cv'] = df['contract_number'].apply(contract_size)


print(df)