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270 changes: 268 additions & 2 deletions lab-python-functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -43,11 +43,277 @@
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "ea116f06",
"metadata": {},
"source": [
"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."
]
},
{
"cell_type": "code",
"execution_count": 92,
"id": "1b4edc7a",
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(products):\n",
" inventory = {}\n",
" for product in products:\n",
" quantity = int(input(f\"Enter quantity for {product}: \"))\n",
" inventory[product] = quantity\n",
"\n",
" return inventory \n",
"\n",
"\n",
"\n",
" "
]
},
{
"cell_type": "markdown",
"id": "eae64637",
"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."
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "19f666d3",
"metadata": {},
"outputs": [],
"source": [
"def get_customer_orders():\n",
" customer_orders = set()\n",
" continue_entering = \"yes\"\n",
"\n",
" while continue_entering == \"yes\":\n",
" product = input(\"Enter a product to order: \")\n",
" customer_orders.add(product)\n",
"\n",
" continue_entering = input(\"Do you want to add another product? (yes/no): \")\n",
"\n",
" return customer_orders \n"
]
},
{
"cell_type": "markdown",
"id": "ca65de03",
"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."
]
},
{
"cell_type": "code",
"execution_count": 90,
"id": "9b21298f",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory):\n",
" for product in customer_orders:\n",
" if product in inventory and inventory[product] > 0:\n",
" inventory[product] = inventory[product]-1\n"
]
},
{
"cell_type": "markdown",
"id": "5cf559be",
"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."
]
},
{
"cell_type": "code",
"execution_count": 102,
"id": "185c1522",
"metadata": {},
"outputs": [],
"source": [
"def calculate_order_statistics(customer_orders, products):\n",
" \n",
" total_products_available=len(products)\n",
" total_products_ordered=len(customer_orders)\n",
" percentage_ordered=(total_products_ordered/total_products_available)*100\n",
"\n",
" return total_products_available, percentage_ordered"
]
},
{
"cell_type": "markdown",
"id": "f300d0dc",
"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."
]
},
{
"cell_type": "code",
"execution_count": 108,
"id": "eeee4913",
"metadata": {},
"outputs": [],
"source": [
"def print_order_statistics(order_statistics):\n",
" total_products_ordered, percentage_ordered = order_statistics\n",
" print(\"***Order Statistics: ***\")\n",
" print(f\"Total Products Ordered: {total_products_ordered} \")\n",
" print(f\"Percentage of Products Ordered: {percentage_ordered}%\")\n",
"\n",
" \n",
" "
]
},
{
"cell_type": "markdown",
"id": "56c01852",
"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."
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "ffc3287c",
"metadata": {},
"outputs": [],
"source": [
"def print_updated_inventory(inventory):\n",
" for product, quantity in inventory.items():\n",
" print(f\"{product}: {quantity}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "51337b8b",
"metadata": {},
"outputs": [],
"source": [
"7. Call the functions in the appropriate sequence to execute the program and manage customer orders."
]
},
{
"cell_type": "code",
"execution_count": 94,
"id": "21c80e1e",
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"inventory=initialize_inventory(products)"
]
},
{
"cell_type": "code",
"execution_count": 95,
"id": "44842ab7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 4, 'mug': 5, 'hat': 6, 'book': 7, 'keychain': 8}\n"
]
}
],
"source": [
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 97,
"id": "6a3c22d3",
"metadata": {},
"outputs": [],
"source": [
"customer_orders=get_customer_orders()\n"
]
},
{
"cell_type": "code",
"execution_count": 98,
"id": "c3cb64c1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 4, 'mug': 4, 'hat': 5, 'book': 7, 'keychain': 8}\n"
]
}
],
"source": [
"update_inventory(customer_orders, inventory)\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 103,
"id": "9e116450",
"metadata": {},
"outputs": [],
"source": [
"order_statistics= calculate_order_statistics(customer_orders, products)"
]
},
{
"cell_type": "code",
"execution_count": 109,
"id": "6b200af8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"***Order Statistics: ***\n",
"Total Products Ordered: 5 \n",
"Percentage of Products Ordered: 40.0%\n"
]
}
],
"source": [
"print_order_statistics(order_statistics)"
]
},
{
"cell_type": "code",
"execution_count": 110,
"id": "d10bbcc3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"t-shirt: 4\n",
"mug: 4\n",
"hat: 5\n",
"book: 7\n",
"keychain: 8\n"
]
}
],
"source": [
"print_updated_inventory(inventory)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "base",
"language": "python",
"name": "python3"
},
Expand All @@ -61,7 +327,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.9"
}
},
"nbformat": 4,
Expand Down