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lab-python-data-structures.ipynb #583

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lab-python-data-structures.ipynb
rmoind Oct 7, 2025
690af56
lab-python-data-structures.ipynb
rmoind Oct 7, 2025
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336 changes: 334 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 +50,343 @@
"\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": [
"#1. \n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"list"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(products)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#2.\n",
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"dict"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 7, 'mug': 6, 'hat': 5, 'book': 4, 'keychain': 3}\n"
]
}
],
"source": [
"#3.\n",
"for product in products:\n",
" quantity = int(input(f\"Enter the quantity for {product}: \"))\n",
" inventory[product] = quantity\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"dict_items([('t-shirt', 7), ('mug', 6), ('hat', 5), ('book', 4), ('keychain', 3)])"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"for product in products:\n",
" quantity = int(input(f\"Enter the quantity for {product}: \"))\n",
" inventory[product] = quantity\n",
"inventory.items()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"# 4. \n",
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"set"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"# 5.\n",
"for i in range(3):\n",
" order = input(\"Enter the name of a product to order (t-shirt, mug, hat, book, keychain): \")\n",
" if order in products:\n",
" customer_orders.add(order)\n",
" else:\n",
" print(f\"{order} is not available in the product list.\")"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'book', 'hat', 'mug'}"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"customer_orders"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'book', 'mug', 'hat'}\n"
]
}
],
"source": [
"# 6.\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 7.\n",
"total_products_ordered = len(customer_orders)\n",
"len(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"percentage_of_products_ordered = (total_products_ordered / len(products)) * 100"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"order_status = (total_products_ordered, percentage_of_products_ordered)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(3, 60.0)"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_status"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tuple"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(order_status)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 60.0% \n"
]
}
],
"source": [
"# 8.\n",
"print(\"Order Statistics:\")\n",
"print(f\"Total Products Ordered: {total_products_ordered}\")\n",
"print(f\"Percentage of Products Ordered: {percentage_of_products_ordered}% \")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 6, 'mug': 5, 'hat': 4, 'book': 3, 'keychain': 2}\n"
]
}
],
"source": [
"# 9.\n",
"for product in products:\n",
" inventory[product] -= 1\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"t-shirt: 6\n",
"mug: 5\n",
"hat: 4\n",
"book: 3\n",
"keychain: 2\n"
]
}
],
"source": [
"# 10.\n",
"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"
},
Expand All @@ -68,7 +400,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.7"
}
},
"nbformat": 4,
Expand Down