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Update lab-python-data-structures.ipynb #652

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174 changes: 172 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 +50,181 @@
"\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": [
"#paso 1-Creo la lista de productos\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#paso 2-Creo el diccionario vacío\n",
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Introduce la cantidad disponible de cada producto:\n"
]
}
],
"source": [
"#paso 3-Pido al usuario la cantidad de cada producto\n",
"print(\"Introduce la cantidad disponible de cada producto:\")\n",
"for product in products:\n",
" quantity = int(input(f\"{product}: \"))\n",
" inventory[product] = quantity\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 12, 'mug': 23, 'hat': 21, 'book': 44, 'keychain': 64}\n"
]
}
],
"source": [
"#compruebo el inventario\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#paso 5- Pedir 3 productos al cliente\n",
"print(\"Introduce 3 productos que el cliente quiere comprar:\")\n",
"\n",
"while len(customer_orders) < 3:\n",
" product = input(\"Producto: \").lower()\n",
"\n",
" if product in products:\n",
" customer_orders.add(product)\n",
" else:\n",
" print(\"Producto inválido. Usa uno de estos:\", products)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Productos pedidos:\n"
]
},
{
"ename": "NameError",
"evalue": "name 'customer_orders' is not defined",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mNameError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[8]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m#paso 6-Mostrar los productos pedidos\u001b[39;00m\n\u001b[32m 2\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mProductos pedidos:\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[43mcustomer_orders\u001b[49m)\n",
"\u001b[31mNameError\u001b[39m: name 'customer_orders' is not defined"
]
}
],
"source": [
"#paso 6-Mostrar los productos pedidos\n",
"print(\"Productos pedidos:\")\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'customer_orders' is not defined",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mNameError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[9]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m#paso 7- Calcular estadísticas del pedido\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m total_products_ordered = \u001b[38;5;28mlen\u001b[39m(\u001b[43mcustomer_orders\u001b[49m)\n\u001b[32m 3\u001b[39m percentage_ordered = (total_products_ordered / \u001b[38;5;28mlen\u001b[39m(products)) * \u001b[32m100\u001b[39m\n\u001b[32m 5\u001b[39m order_status = (total_products_ordered, percentage_ordered)\n",
"\u001b[31mNameError\u001b[39m: name 'customer_orders' is not defined"
]
}
],
"source": [
"#paso 7- Calcular estadísticas del pedido\n",
"total_products_ordered = len(customer_orders)\n",
"percentage_ordered = (total_products_ordered / len(products)) * 100\n",
"\n",
"order_status = (total_products_ordered, percentage_ordered)\n",
"print(\"Estado del pedido (total productos, porcentaje del inventario):\", order_status)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#paso 8- mostrar las estadisticas del pedido\n",
"print(\"Order Statistics:\")\n",
"print(\"Total Products Ordered:\", order_status[0])\n",
"print(\"Percentage of Products Ordered:\", order_status[1], \"%\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#paso 9- actualizamos el inventario\n",
"for product in customer_orders:\n",
" inventory[product] -= 1\n",
"print(\"Inventario actualizado:\", inventory)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#paso 10- mostramos el inventario actualizado\n",
"print(\"Inventario actualizado:\")\n",
"\n",
"for product, quantity in inventory.items():\n",
" print(product, \":\", quantity)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -68,7 +238,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.14.0"
}
},
"nbformat": 4,
Expand Down