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‎lab-python-functions.ipynb‎

Lines changed: 269 additions & 3 deletions
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@@ -43,13 +43,279 @@
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "40e1d6ad-fa61-43d2-84a5-b68844b7c778",
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"metadata": {},
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"outputs": [],
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"source": [
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"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 180,
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"id": "327bde1e-5ffe-4d17-93dc-207741327ea0",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Define a function named initialize_inventory that takes products as a parameter. \n",
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"#Inside the function, implement the code for initializing the inventory dictionary using a loop and user input.\n",
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"def initialize_inventory(products):\n",
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" inventory = {}\n",
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" \"\"\"Shows the number of each item\"\"\"\n",
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" for item in products:\n",
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" number_of_items = int(input(\"Number of \" + item + \": \")) \n",
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" inventory[item] = number_of_items\n",
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" print (inventory)\n",
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" return inventory "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 168,
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"id": "35135cb7-d43b-4537-b5ea-f0ba9d2a3bf6",
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"metadata": {},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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"Number of t-shirt: 10\n",
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"Number of mug: 10\n",
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"Number of hat: 10\n",
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"Number of book: 10\n",
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"Number of keychain: 10\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'t-shirt': 10, 'mug': 10, 'hat': 10, 'book': 10, 'keychain': 10}\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"{'t-shirt': 10, 'mug': 10, 'hat': 10, 'book': 10, 'keychain': 10}"
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]
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},
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"execution_count": 168,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"initialize_inventory(products)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 172,
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"id": "7a2437ca-3681-49e0-8898-fe6f4067b1fd",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Define a function named get_customer_orders that takes no parameters. \n",
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"# Inside the function, implement the code for prompting the user to enter the product names using a loop. \n",
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"# The function should return the customer_orders set.\n",
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"\n",
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"def get_customer_orders ():\n",
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" customer_orders = set ()\n",
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" answer = \"yes\"\n",
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" while answer == \"yes\":\n",
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" product = input(\"Choose a product: \")\n",
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" customer_orders.add(product)\n",
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" answer = input(\"Do you want something else? (yes/no): \").lower()\n",
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" print (\"customer_ order\", customer_orders) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 173,
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"id": "d088eabd-adf4-4a04-a61e-fd3f4326ccd8",
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"metadata": {},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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"Choose a product: book\n",
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"Do you want something else? (yes/no): yes\n",
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"Choose a product: hat\n",
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"Do you want something else? (yes/no): no\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"customer_ order {'book', 'hat'}\n"
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]
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}
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],
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"source": [
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"get_customer_orders ()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 181,
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"id": "86be53b5-2c9a-4f21-bd05-cccb95e47b6a",
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"metadata": {},
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"outputs": [],
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"source": [
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"#3. Define a function named `update_inventory` that takes `customer_orders` and `inventory` as parameters. \n",
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"# Inside the function, implement the code for updating the inventory dictionary based on the customer orders.\n",
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"\n",
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"\n",
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"def updated_inventory (customer_orders, inventory):\n",
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" new_inventory = {}\n",
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" for item in customer_orders:\n",
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" if item in inventory:\n",
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" inventory [item]-= 1\n",
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" return inventory \n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 182,
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"id": "2c940a7e-9af8-4aa5-a9d3-86739c75f715",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'t-shirt': 1, 'mug': 0, 'hat': 0, 'book': 0, 'keychain': 1}"
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]
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},
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"execution_count": 182,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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" updated_inventory (customer_orders, inventory)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 213,
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"id": "941ac3fb-0f28-480c-bf8b-795e30f987b6",
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"metadata": {},
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"outputs": [],
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"source": [
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"# 4 Define a function named calculate_order_statistics that takes customer_orders and products as parameters. \n",
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"#Inside the function, implement the code for calculating the order statistics \n",
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"#(total products ordered, and percentage of unique products ordered). \n",
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"#The function should return these values.\n",
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"\n",
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"def calculate_order_statistics(customer_orders, products):\n",
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" total = len(customer_orders)\n",
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" percentage = len(customer_orders) * 100 / len(products)\n",
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" return total, percentage"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 212,
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"id": "ad5111f1-f623-4dfb-ae9d-8015a30da88d",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(4, 80.0)"
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]
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},
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"execution_count": 212,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"calculate_order_statistics (customer_orders, products)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 219,
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"id": "8caaeaef-81c9-4dc4-98a0-dba2558dd29f",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"4\n",
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"80.0\n"
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]
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}
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],
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"source": [
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"# Define a function named `print_order_statistics` that takes `order_statistics` as a parameter. \n",
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"# Inside the function, implement the code for printing the order statistics.\n",
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"\n",
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"def print_order_statistics(order_statistics):\n",
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" total, percentage = order_statistics\n",
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" print(total)\n",
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" print(percentage)\n",
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"\n",
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"stats = calculate_order_statistics(customer_orders, products)\n",
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"print(stats[0]) # total\n",
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"print(stats[1]) # percentage \n",
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" \n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 222,
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"id": "f1d59425-db7c-4b75-bf22-ab8ee0403f06",
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"metadata": {},
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"outputs": [],
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"source": [
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"# 6. Define a function named `print_updated_inventory` that takes `inventory` as a parameter. \n",
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"#Inside the function, implement the code for printing the updated inventory.\n",
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"\n",
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"def print_updated_inventory (inventory):\n",
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" print(inventory)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 221,
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"id": "0156e6a4-0983-4837-a047-b7554944e5ef",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'t-shirt': 1, 'mug': 0, 'hat': 0, 'book': 0, 'keychain': 1}\n"
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]
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}
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],
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"source": [
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"print_updated_inventory (inventory)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0242022c-ead2-4c8c-94d5-ff986479ae10",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"display_name": "Python [conda env:base] *",
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"language": "python",
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"name": "python3"
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"name": "conda-base-py"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.13"
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"version": "3.13.5"
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}
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},
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"nbformat": 4,

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