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Completed functions lab #683

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285 changes: 285 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"
]
},
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"cell_type": "markdown",
"id": "0c581062-8967-4d93-b06e-62833222f930",
"metadata": {
"tags": []
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"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": "markdown",
"id": "5ab31e78-b58d-486b-8359-32eaa22b2463",
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"source": [
"## Functions"
]
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"execution_count": 1,
"id": "2b746a12-1c40-4eed-8b66-f8512ce15fcc",
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"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"\n",
"def initialize_inventory(products):\n",
" inventory = {}\n",
" \n",
" for product in products:\n",
" quantity = int(input(\"Please add the number of items for \" + product))\n",
" inventory[product] = quantity\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "68883983-edff-4fde-9597-c0c3b8b0de42",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please add the number of items for t-shirt 10\n",
"Please add the number of items for mug 8\n",
"Please add the number of items for hat 5\n",
"Please add the number of items for book 12\n",
"Please add the number of items for keychain 4\n"
]
}
],
"source": [
"inventory = initialize_inventory(products)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "64ba8010-09c4-4b37-af52-6461d89fafd2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 10, 'mug': 8, 'hat': 5, 'book': 12, 'keychain': 4}\n"
]
}
],
"source": [
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "ea3e3161-c25e-4f83-92bd-314d33de275d",
"metadata": {},
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"source": [
"def get_customer_orders():\n",
" customer_orders = set()\n",
" order_again = \"yes\"\n",
" \n",
" while order_again == \"yes\":\n",
" product = input(\"Please add the product you would like to order:\").lower().strip()\n",
" customer_orders.add(product)\n",
" order_again = input(\"Would you like to continue ordering? Please answer with yes or no.\").lower().strip()\n",
"\n",
" print (\"Thank you for your order!\")\n",
" return customer_orders"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a79abe87-66a2-440c-8e04-2c0782aca7ad",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please add the product you would like to order: mug\n",
"Would you like to continue ordering? Please answer with yes or no. yes\n",
"Please add the product you would like to order: t-shirt\n",
"Would you like to continue ordering? Please answer with yes or no. yes\n",
"Please add the product you would like to order: book\n",
"Would you like to continue ordering? Please answer with yes or no. yes\n",
"Please add the product you would like to order: keychain\n",
"Would you like to continue ordering? Please answer with yes or no. no\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Thank you for your order!\n"
]
}
],
"source": [
"customer_orders = get_customer_orders()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "8802498b-a518-4c08-bcba-b7d69ebd1bc3",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory):\n",
" for product in customer_orders:\n",
" inventory[product]-=1\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "972e04a2-c2af-4356-8112-54bf7edce601",
"metadata": {},
"outputs": [],
"source": [
"inventory = update_inventory(customer_orders, inventory)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "787d4744-8224-412a-8986-59b6bca348b3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 9, 'mug': 7, 'hat': 5, 'book': 11, 'keychain': 3}"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inventory"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "c008ba87-10d3-4061-a700-3fcc23f6d058",
"metadata": {},
"outputs": [],
"source": [
"def calculate_order_statistics(customer_orders, products):\n",
" total_products_ordered = len(customer_orders)\n",
" percentage_unique_products_ordered = (total_products_ordered / len(products))*100\n",
" return total_products_ordered, percentage_unique_products_ordered"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "3958a306-aef9-49ca-b40b-d7af24218c10",
"metadata": {},
"outputs": [],
"source": [
"order_statistics = calculate_order_statistics(customer_orders, products)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "5d79e8d9-e994-437f-9125-8ea7633c407e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(4, 80.0)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_statistics"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "608d0bf9-7ae1-4f0e-beb3-110b30b067b3",
"metadata": {},
"outputs": [],
"source": [
"##to be continued"
]
}
],
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