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Lab Data Structures solved #626

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202 changes: 199 additions & 3 deletions lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -50,13 +50,209 @@
"\n",
"Solve the exercise by implementing the steps using the Python concepts of lists, dictionaries, sets, and basic input/output operations. "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please, enter the quantity of t-shirt in stock: 34\n",
"Please, enter the quantity of mug in stock: 2\n",
"Please, enter the quantity of hat in stock: 12\n",
"Please, enter the quantity of book in stock: 5\n",
"Please, enter the quantity of keychain in stock: 32\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 34, 'mug': 2, 'hat': 12, 'book': 5, 'keychain': 32}\n"
]
}
],
"source": [
"for product in products:\n",
" quantity = int(input(f\"Please, enter the quantity of {product} in stock: \"))\n",
" inventory[product] = quantity\n",
"\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please, enter three products to order: book\n",
"Please, enter three products to order: book\n",
"You already ordered that product, enter a different one: hat\n",
"Please, enter three products to order: t-shirt\n"
]
}
],
"source": [
"for i in range(3):\n",
" product = input(\"Please, enter three products to order: \")\n",
" \n",
" while product not in products or product in customer_orders:\n",
" if product not in products:\n",
" product = input(\"Invalid product, try again: \")\n",
" else:\n",
" product = input(\"You already ordered that product, enter a different one: \")\n",
"\n",
" customer_orders.add(product)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Your order includes: {'t-shirt', 'book', 'hat'}\n"
]
}
],
"source": [
"print(f\"Your order includes: {customer_orders}\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(85, 3.5294117647058822)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"total_ordered = len(customer_orders)\n",
"total_products = sum(inventory.values())\n",
" \n",
"percentage_products_ordered= (total_ordered/total_products)*100\n",
"\n",
"order_status= (total_products, percentage_products_ordered)\n",
"order_status"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 3.5294117647058822%\n"
]
}
],
"source": [
"print(f\"Order Statistics:\\nTotal Products Ordered: {total_ordered}\\nPercentage of Products Ordered: {percentage_products_ordered}%\")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order processed\n",
"Order processed\n",
"Order processed\n"
]
}
],
"source": [
"for product in customer_orders: \n",
" if inventory[product] > 0:\n",
" inventory[product] -= 1\n",
" print(\"Order processed\")\n",
" else: \n",
" print(\"Out of stock\")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"t-shirt: 33\n",
"mug: 2\n",
"hat: 11\n",
"book: 4\n",
"keychain: 32\n"
]
}
],
"source": [
"for product, quantity in inventory.items():\n",
" print(f\"{product}: {quantity}\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python [conda env:base] *",
"language": "python",
"name": "python3"
"name": "conda-base-py"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -68,7 +264,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
Expand Down