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Solved lab
sevgiozdemir617-alt Aug 31, 2026
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Solved lab
sevgiozdemir617-alt Aug 31, 2026
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117 changes: 0 additions & 117 deletions README.md
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167 changes: 165 additions & 2 deletions lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -50,11 +50,174 @@
"\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": 1,
"metadata": {},
"outputs": [],
"source": [
"# 1. Create a list containing all available products\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# 2. Create an empty dictionary for the inventory\n",
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# 3. Ask the user for the quantity of each product\n",
"for product in products:\n",
" quantity = int(input(f\"How many {product}s are available? \"))\n",
" inventory[product] = quantity"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# 4. Create an empty set for customer orders\n",
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# 5. Ask the customer to enter three products\n",
"for number in range(3):\n",
" product = input(\n",
" f\"Enter product {number + 1} to order \"\n",
" \"(t-shirt, mug, hat, book, keychain): \"\n",
" ).lower()\n",
"\n",
" customer_orders.add(product)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Products in customer order:\n",
"{'mug', 'hat', 'book'}\n"
]
}
],
"source": [
"# 6. Print the products in the customer order\n",
"print(\"\\nProducts in customer order:\")\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"\n",
"# 7. Calculate the order statistics\n",
"total_products_ordered = len(customer_orders)\n",
"\n",
"percentage_ordered = (\n",
" total_products_ordered / len(products)\n",
") * 100\n",
"\n",
"order_status = (total_products_ordered, percentage_ordered)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Order Statistics:\n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 60.0%\n"
]
}
],
"source": [
"# 8. Print the order statistics\n",
"print(\"\\nOrder Statistics:\")\n",
"print(f\"Total Products Ordered: {order_status[0]}\")\n",
"print(f\"Percentage of Products Ordered: {order_status[1]}%\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# 9. Subtract 1 from the inventory quantity of every product\n",
"for product in products:\n",
" inventory[product] -= 1"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Updated Inventory:\n",
"t-shirt: 19\n",
"mug: 9\n",
"hat: 9\n",
"book: 49\n",
"keychain: 99\n"
]
}
],
"source": [
"# 10. Print the updated inventory\n",
"print(\"\\nUpdated Inventory:\")\n",
"for product in products:\n",
" print(f\"{product}: {inventory[product]}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -68,7 +231,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.9.6"
}
},
"nbformat": 4,
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