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188 changes: 174 additions & 14 deletions lab-python-data-structures.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -2,9 +2,7 @@
"cells": [
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"metadata": {},
"source": [
"# Lab | Data Structures "
]
Expand Down Expand Up @@ -50,27 +48,189 @@
"\n",
"Solve the exercise by implementing the steps using the Python concepts of lists, dictionaries, sets, and basic input/output operations. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**1.** `products` list."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**2.** Empty `inventory` dictionary."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"inventory = {}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**3.** Ask for the quantity of each product and store it in `inventory`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for product in products:\n",
" quantity = int(input(f\"Enter the quantity of {product}s available: \"))\n",
" inventory[product] = quantity"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**4.** Empty `customer_orders` set."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"customer_orders = set()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**5.** Ask for three products the customer wants to order and add them to `customer_orders`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for _ in range(3):\n",
" order = input(\"Enter the name of a product the customer wants to order: \")\n",
" customer_orders.add(order)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**6.** Print the products in `customer_orders`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Products in customer_orders:\", customer_orders)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**7.** Order statistics stored in the `order_status` tuple."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"total_products_ordered = len(customer_orders)\n",
"percentage_ordered = (total_products_ordered / len(products)) * 100\n",
"order_status = (total_products_ordered, percentage_ordered)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**8.** Print the order statistics."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Order Statistics:\")\n",
"print(f\"Total Products Ordered: {order_status[0]}\")\n",
"print(f\"Percentage of Products Ordered: {order_status[1]}%\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**9.** Update the inventory by subtracting 1 from each ordered product."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for product in customer_orders:\n",
" inventory[product] -= 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**10.** Print the updated inventory."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for product, quantity in inventory.items():\n",
" print(f\"{product}: {quantity}\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.x"
}
},
"nbformat": 4,
"nbformat_minor": 4
"nbformat_minor": 5
}