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378 changes: 378 additions & 0 deletions .ipynb_checkpoints/lab-python-functions-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "25d7736c-ba17-4aff-b6bb-66eba20fbf4e",
"metadata": {},
"source": [
"# Lab | Functions"
]
},
{
"cell_type": "markdown",
"id": "0c581062-8967-4d93-b06e-62833222f930",
"metadata": {
"tags": []
},
"source": [
"## Exercise: Managing Customer Orders with Functions\n",
"\n",
"In the previous exercise, you improved the code for managing customer orders by using loops and flow control. Now, let's take it a step further and refactor the code by introducing functions.\n",
"\n",
"Follow the steps below to complete the exercise:\n",
"\n",
"1. Define a function named `initialize_inventory` that takes `products` as a parameter. Inside the function, implement the code for initializing the inventory dictionary using a loop and user input.\n",
"\n",
"2. Define a function named `get_customer_orders` that takes no parameters. Inside the function, implement the code for prompting the user to enter the product names using a loop. The function should return the `customer_orders` set.\n",
"\n",
"3. Define a function named `update_inventory` that takes `customer_orders` and `inventory` as parameters. Inside the function, implement the code for updating the inventory dictionary based on the customer orders.\n",
"\n",
"4. Define a function named `calculate_order_statistics` that takes `customer_orders` and `products` as parameters. Inside the function, implement the code for calculating the order statistics (total products ordered, and percentage of unique products ordered). The function should return these values.\n",
"\n",
"5. Define a function named `print_order_statistics` that takes `order_statistics` as a parameter. Inside the function, implement the code for printing the order statistics.\n",
"\n",
"6. Define a function named `print_updated_inventory` that takes `inventory` as a parameter. Inside the function, implement the code for printing the updated inventory.\n",
"\n",
"7. Call the functions in the appropriate sequence to execute the program and manage customer orders.\n",
"\n",
"Hints for functions:\n",
"\n",
"- Consider the input parameters required for each function and their return values.\n",
"- Utilize function parameters and return values to transfer data between functions.\n",
"- Test your functions individually to ensure they work correctly.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 212,
"id": "85adffbe-9bab-4740-8da6-66ff062f8199",
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(product_names):\n",
" inventory= {}\n",
" for product in product_names:\n",
" quantity = int(input(f\"Enter a quantity for the {product}:\"))\n",
" inventory[product] = quantity #adding a key-value pair to the dictionary called inventory. It stores the quantity input for the given key(product)\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": 213,
"id": "6467242a-39db-4d2c-8d2f-cc07597bca27",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter a quantity for the t-shirt: 45\n",
"Enter a quantity for the mug: 4\n",
"Enter a quantity for the hat: 6\n",
"Enter a quantity for the book: 4\n",
"Enter a quantity for the keychain: 0\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 45, 'mug': 4, 'hat': 6, 'book': 4, 'keychain': 0}\n"
]
}
],
"source": [
"product_names = [\"t-shirt\",\"mug\",\"hat\",\"book\",\"keychain\"]\n",
"inventory = initialize_inventory(product_names) #call for the function and save result in inventory\n",
"print(inventory) "
]
},
{
"cell_type": "code",
"execution_count": 214,
"id": "f0cea770-1624-4ab2-9fbe-6d54d12ff8bc",
"metadata": {},
"outputs": [],
"source": [
"def get_customer_orders(product_names):\n",
" customer_orders={}\n",
" for product in product_names:\n",
" customer_order = int(input(f\"Enter the quantity of {product} you want to buy:\"))\n",
" customer_orders[product] = customer_order\n",
" return customer_orders\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 215,
"id": "0f8bf2ff-add6-4d87-af4f-985719a2ca77",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter the quantity of t-shirt you want to buy: 34\n",
"Enter the quantity of mug you want to buy: 0\n",
"Enter the quantity of hat you want to buy: 4\n",
"Enter the quantity of book you want to buy: 7\n",
"Enter the quantity of keychain you want to buy: 3\n"
]
}
],
"source": [
"customer_orders=get_customer_orders(product_names)"
]
},
{
"cell_type": "code",
"execution_count": 216,
"id": "e8212937-3966-49c5-8b32-1d5c1edb1cd3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 34, 'mug': 0, 'hat': 4, 'book': 7, 'keychain': 3}"
]
},
"execution_count": 216,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"customer_orders"
]
},
{
"cell_type": "code",
"execution_count": 217,
"id": "725e64b2-0b2e-4c84-8611-7d0c656e0ebf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4"
]
},
"execution_count": 217,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"customer_orders['hat']"
]
},
{
"cell_type": "code",
"execution_count": 218,
"id": "169e280b-c1cf-425f-8e02-ec29dfcd9dd1",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory): \n",
" for product, quantity in customer_orders.items():\n",
" if product in inventory:\n",
" inventory[product] -= customer_orders[product]\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": 219,
"id": "23d056f3-dbcd-493e-98d5-34592e56aa99",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 11, 'mug': 4, 'hat': 2, 'book': -3, 'keychain': -3}"
]
},
"execution_count": 219,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"update_inventory(customer_orders, inventory)"
]
},
{
"cell_type": "code",
"execution_count": 220,
"id": "790f744e-ddaf-40b5-ac8a-68f2acc33bb2",
"metadata": {},
"outputs": [],
"source": [
"sum_products_ordered=sum(customer_orders.values())\n",
"Percentage_of_products_ordered = round((sum(customer_orders.values())/sum(inventory.values()))*100,2)\n",
"def calculate_order_statistics(customer_orders, products):\n",
" sum_products_ordered=sum(customer_orders.values())\n",
" Percentage_of_products_ordered = round((sum(customer_orders.values())/sum(inventory.values()))*100,2)\n",
" return sum_products_ordered, Percentage_of_products_ordered"
]
},
{
"cell_type": "code",
"execution_count": 221,
"id": "9a3e1ba5-ec50-4a81-95e1-96b4dde2ccd9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(48, 436.36)"
]
},
"execution_count": 221,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"calculate_order_statistics(customer_orders, products)\n"
]
},
{
"cell_type": "code",
"execution_count": 222,
"id": "1ce871b8-2ef2-4a11-b834-2b64a24904c5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"48"
]
},
"execution_count": 222,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum_products_ordered"
]
},
{
"cell_type": "code",
"execution_count": 223,
"id": "7ae583d9-5ba3-457c-9fb0-fcdcffa30faa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"436.36"
]
},
"execution_count": 223,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Percentage_of_products_ordered"
]
},
{
"cell_type": "code",
"execution_count": 224,
"id": "27cc73b1-e2dc-45b8-9f0a-9d19f9c23137",
"metadata": {},
"outputs": [],
"source": [
"def print_order_statistics(sum_products_ordered, Percentage_of_products_ordered):\n",
" print(f\"Total Products Ordered: {sum_products_ordered}\")\n",
" print(f\"Percentage of Inventory Ordered: {Percentage_of_products_ordered}%\")\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 225,
"id": "e6ac6341-a297-46c7-a687-eff43d71dcae",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total Products Ordered: 48\n",
"Percentage of Inventory Ordered: 436.36%\n"
]
}
],
"source": [
"print_order_statistics(sum_products_ordered, Percentage_of_products_ordered)"
]
},
{
"cell_type": "code",
"execution_count": 226,
"id": "24cc9db4-6cda-4405-845b-8cff9b8fae2d",
"metadata": {},
"outputs": [],
"source": [
"def print_order_statistics(inventory):\n",
" print(f\"Updated Inventory:{inventory}\")\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 227,
"id": "2cc96888-71f5-43df-a37a-6bf91af984b0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Updated Inventory:{'t-shirt': 11, 'mug': 4, 'hat': 2, 'book': -3, 'keychain': -3}\n"
]
}
],
"source": [
"print_order_statistics(inventory)"
]
},
{
"cell_type": "markdown",
"id": "f026e89b-96ba-40c4-8855-117500c5eacb",
"metadata": {},
"source": [
"#### "
]
}
],
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"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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"version": "3.13.5"
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},
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}
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