Analyses Tesco-Customer-Data.json and gives you useless statistics about your order history

tesco-analysis.py

#!/usr/bin/python3
import json
import math

with open('Tesco-Customer-Data.json') as json_file:
    data = json.load(json_file)

orders = []
for purchase_block in data['Purchase']:
    for purchase in purchase_block:
        orders.append(purchase)

items = {}
for order in orders:
    for product in order['product']:

        if product['name'] in items:
            items[product['name']]['money_spent'] += float(product['price'])
            items[product['name']]['quantity'] += float(product['quantity'])

        else:
            items[product['name']] = {}
            items[product['name']]['name'] = product['name']
            items[product['name']]['money_spent'] = float(product['price'])
            items[product['name']]['quantity'] = float(product['quantity'])

to_delete = []
for key, item in items.items():
    if item['quantity'] == 0:
        to_delete.append(key)

for key in to_delete:
    del items[key]

most_expensive = sorted(items.values(), key=lambda k: k['money_spent'], reverse=True)
most_bought = sorted(items.values(), key=lambda k: k['quantity'], reverse=True)

print("You spent the most money on...\n")
for item in most_expensive[:10]:
    print("%s (%s items for £%s)" % (item['name'], math.ceil(item['quantity']), round(item['money_spent'], 2)))


print("\n\nAnd you bought these items most frequently...\n")
for item in most_bought[:10]:
    print("%s (%s items for £%s)" % (item['name'], math.ceil(item['quantity']), round(item['money_spent'], 2)))