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Update lab-python-data-structures.ipynb #764

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166 changes: 164 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 +50,173 @@
"\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": null,
"metadata": {},
"outputs": [],
"source": [
"# This is Kyle Solving the Lab"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"products=[\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"inventory={}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Ask for product inventory\n",
"inventory[\"t-shirt\"] = int(input(\"Enter the quantity of t-shirt: \"))\n",
"inventory[\"mug\"] = int(input(\"Enter the quantity of mug: \"))\n",
"inventory[\"hat\"] = int(input(\"Enter the quantity of hat: \"))\n",
"inventory[\"book\"] = int(input(\"Enter the quantity of book: \"))\n",
"inventory[\"keychain\"] = int(input(\"Enter the quantity of keychain: \"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"customer_orders=set()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Ask for orders\n",
"product_order_1 = input(\"Enter the first product: \")\n",
"product_order_2 = input(\"Enter the second product: \")\n",
"product_order_3 = input(\"Enter the third product: \")\n",
"customer_orders.add(product_order_1)\n",
"customer_orders.add(product_order_2)\n",
"customer_orders.add(product_order_3)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(customer_orders)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"percentage_ordered = (len(customer_orders) / len(products)) * 100\n",
"print(f\"percentage of products ordered: {percentage_ordered}%\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"order_status=(total_products_ordered, percentage_ordered)\n",
"print(order_status)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Memory update\n",
"inventory[product_order_1] = inventory[product_order_1] - 1\n",
"inventory[product_order_2] = inventory[product_order_2] - 1\n",
"inventory[product_order_3] = inventory[product_order_3] - 1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Inventory update\n",
"print(f\"t-shirt: {inventory['t-shirt']}\")\n",
"print(f\"mug: {inventory['mug']}\")\n",
"print(f\"hat: {inventory['hat']}\")\n",
"print(f\"book: {inventory['book']}\")\n",
"print(f\"keychain: {inventory['keychain']}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"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 +230,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.10.4"
}
},
"nbformat": 4,
Expand Down