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Lab Data Structures Terminado #578

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Update lab-python-data-structures.ipynb
ignaciosabatell Oct 6, 2025
4b4411c
Update lab-python-data-structures.ipynb
ignaciosabatell Oct 6, 2025
9cc7bd5
Update lab-python-data-structures.ipynb
ignaciosabatell Oct 6, 2025
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Update lab-python-data-structures.ipynb
ignaciosabatell Oct 7, 2025
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222 changes: 220 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 +50,229 @@
"\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": 61,
"metadata": {},
"outputs": [],
"source": [
"#1. Define a list called `products` that contains the following items: \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"products= [\"tshirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#2. Create an empty dictionary called `inventory`."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"#3. Ask the user to input the quantity of each product available in the inventory. Use the product names from the `products` list as keys in the `inventory` dictionary and assign the respective quantities as values.\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"valor_tshirt = int(input(\"Enter the quantity of tshirts available: \"))\n",
"valor_mug = int(input(\"Enter the quantity of mugs available: \"))\n",
"valor_hat = int(input(\"Enter the quantity of hats available: \"))\n",
"valor_book = int(input(\"Enter the quantity of books available: \"))\n",
"valor_keychain = int(input(\"Enter the quantity of keychains available: \"))"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [],
"source": [
"#4. Create an empty set called `customer_orders`."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"customer_order = ()"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {},
"outputs": [],
"source": [
"#5. Ask the user to input the name of three products that a customer wants to order (from those in the products list, meaning three products out of \"t-shirt\", \"mug\", \"hat\", \"book\" or \"keychain\". Add each product name to the `customer_orders` set."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"products = [\"tshirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"customer_orders = set()\n",
"product1 = input(\"Ingresa el nombre del primer producto que deseas: \").lower()\n",
"product2 = input(\"Ingresa el nombre del segundo producto que deseas: \").lower()\n",
"product3 = input(\"Ingresa el nombre del tercer producto que deseas: \").lower()\n",
"customer_orders.add(product1)\n",
"customer_orders.add(product2)\n",
"customer_orders.add(product3)"
]
},
{
"cell_type": "code",
"execution_count": 103,
"metadata": {},
"outputs": [],
"source": [
"#6. Print the products in the `customer_orders` set."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'hat', 'tshirt', 'mug'}\n"
]
}
],
"source": [
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"#7. Calculate the following order statistics:\n",
"#. Total Products Ordered: The total number of products in the `customer_orders` set.\n",
"# Percentage of Products Ordered: The percentage of products ordered compared to the total available products."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order statistics:\n",
"Total products ordered: 3\n",
"Percentage of products ordered: 60.0%\n"
]
}
],
"source": [
"total_products_ordered = len(customer_orders)\n",
"percentage_ordered = (total_products_ordered / len(products)) * 100\n",
"order_status = (total_products_ordered, percentage_ordered)\n",
"print(\"Order statistics:\")\n",
"print(f\"Total products ordered: {order_status[0]}\")\n",
"print(f\"Percentage of products ordered: {order_status[1]}%\")\n"
]
},
{
"cell_type": "code",
"execution_count": 124,
"metadata": {},
"outputs": [],
"source": [
"#9. Update the inventory by subtracting 1 from the quantity of each product. Modify the `inventory` dictionary accordingly."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"inventory[\"tshirt\"] = valor_tshirt - 1\n",
"inventory[\"mug\"] = valor_mug - 1\n",
"inventory[\"hat\"] = valor_hat - 1\n",
"inventory[\"book\"] = valor_book - 1\n",
"inventory[\"keychain\"] = valor_keychain - 1"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Updated inventory:\n",
"t-shirt: 4\n",
"mug: 4\n",
"hat: 4\n",
"book: 4\n",
"keychain: 4\n"
]
}
],
"source": [
"print(\"Updated inventory:\")\n",
"print(\"t-shirt:\", inventory[\"tshirt\"])\n",
"print(\"mug:\", inventory[\"mug\"])\n",
"print(\"hat:\", inventory[\"hat\"])\n",
"print(\"book:\", inventory[\"book\"])\n",
"print(\"keychain:\", inventory[\"keychain\"])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "base",
"language": "python",
"name": "python3"
},
Expand All @@ -68,7 +286,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
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