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Finished lab #534

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317 changes: 308 additions & 9 deletions lab-python-functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -22,32 +22,331 @@
"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",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "dd00d8c9",
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(products):\n",
" inventory = {}\n",
" for product in products:\n",
" inventory[product] = int(input(f\"How many {product}s do you have in storage?\"))\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "5ba3b18f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 45, 'mug': 98, 'hat': 34, 'book': 98, 'keychain': 50}"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inventory = initialize_inventory([\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"])\n",
"inventory"
]
},
{
"cell_type": "markdown",
"id": "ebbc8c39",
"metadata": {},
"source": [
"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"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "451c5596",
"metadata": {},
"outputs": [],
"source": [
"def get_customer_orders():\n",
" products = []\n",
" still_buying = True\n",
" while still_buying:\n",
" product = input(\"What products would you like to buy?\")\n",
" customer_answer = input(\"Do you wish to buy another product? (Y/N)\")\n",
"\n",
" # if customer_answer not in [\"Y\", \"N\"]:\n",
" # customer_answer = input(\"Do you wish to buy another product? (Y/N)\")\n",
" if customer_answer == \"N\":\n",
" still_buying = False\n",
"\n",
" products.append(product)\n",
" return products"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "be3ee4c8",
"metadata": {},
"outputs": [],
"source": [
"customer_orders = get_customer_orders()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "84812d28",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['iguana', 'mug', 'book', 't-shirt', '', 'non']"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"customer_orders"
]
},
{
"cell_type": "markdown",
"id": "dc7f1fde",
"metadata": {},
"source": [
"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",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "c365da88",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory):\n",
" # update the inventory dictionary based on customer orders\n",
" # first check the products that the customer bought one at a time\n",
" for product in customer_orders:\n",
" # see if I have the products in the inventory\n",
" if product in inventory:\n",
" # if I do have the product in inventory, remove 1 item of that product from the inventory\n",
" inventory[product] -= 1\n",
" # if I don't have the product in inventory, let the customer know it's not there\n",
" else:\n",
" print(f\"{product} is not in inventory!\")\n",
" # break\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "87d4432a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"iguana is not in inventory!\n",
" is not in inventory!\n",
"non is not in inventory!\n"
]
},
{
"data": {
"text/plain": [
"{'t-shirt': 44, 'mug': 97, 'hat': 34, 'book': 97, 'keychain': 50}"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"update_inventory(customer_orders, inventory)"
]
},
{
"cell_type": "markdown",
"id": "e1e0f6d0",
"metadata": {},
"source": [
"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"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "18de36f4",
"metadata": {},
"outputs": [],
"source": [
"def calculate_order_statistics(customer_orders, products):\n",
" total_products_ordered = len(customer_orders)\n",
" unique_products_ordered = len(set(customer_orders))\n",
" if len(products) > 0:\n",
" percentage_unique_products_ordered = (unique_products_ordered / len(products)) * 100\n",
" else:\n",
" percentage_unique_products_ordered = 0\n",
" return total_products_ordered, percentage_unique_products_ordered\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "84b82824",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(6, 120.0)"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"calculate_order_statistics(customer_orders, [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"])"
]
},
{
"cell_type": "markdown",
"id": "e6c4506d",
"metadata": {},
"source": [
"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"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "d28d2b3f",
"metadata": {},
"outputs": [],
"source": [
"order_statistics = calculate_order_statistics(customer_orders, [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"])"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "37306f19",
"metadata": {},
"outputs": [],
"source": [
"def print_order_statistics(order_statistics):\n",
" print(\"Total products ordered:\", order_statistics[0])\n",
" print(\"Percentage of unique products ordered:\", order_statistics[1], \"%\")\n"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "8969a017",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total products ordered: 6\n",
"Percentage of unique products ordered: 120.0 %\n"
]
}
],
"source": [
"print_order_statistics(order_statistics)"
]
},
{
"cell_type": "markdown",
"id": "442fac5b",
"metadata": {},
"source": [
"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",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "90cd8df1",
"metadata": {},
"outputs": [],
"source": [
"def print_updated_inventory(inventory):\n",
" for product, quantity in inventory.items():\n",
" print(product + \":\", quantity)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "b228e0eb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"t-shirt: 44\n",
"mug: 97\n",
"hat: 34\n",
"book: 97\n",
"keychain: 50\n"
]
}
],
"source": [
"print_updated_inventory(inventory)"
]
},
{
"cell_type": "markdown",
"id": "c55c3a7c",
"metadata": {},
"source": [
"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"
"- Test your functions individually to ensure they work correctly."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "base",
"language": "python",
"name": "python3"
},
Expand All @@ -61,7 +360,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
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