data-structure

lab-python-data-structures.ipynb

@@ -50,11 +50,107 @@
     "\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": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Productos pedidos:\n",
+      "mug\n",
+      "t-shirt\n",
+      "hat\n",
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Products Ordered: 60.00%\n",
+      "Inventario actualizado:\n",
+      "t-shirt: 5\n",
+      "mug: 5\n",
+      "hat: 7\n",
+      "book: 15\n",
+      "keychain: 22\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Paso 1\n",
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "\n",
+    "# Paso 2\n",
+    "inventory = {}\n",
+    "\n",
+    "# Paso 3\n",
+    "\n",
+    "\n",
+    "cantidad_tshirt = int(input(\"¿Cuánt@s t-shirt hay en inventario? \"))\n",
+    "cantidad_mug = int(input(\"¿Cuánt@s mug hay en inventario? \"))\n",
+    "cantidad_hat = int(input(\"¿Cuánt@s hat hay en inventario? \"))\n",
+    "cantidad_book = int(input(\"¿Cuánt@s book hay en inventario? \"))\n",
+    "cantidad_keychain = int(input(\"¿Cuánt@s keychain hay en inventario? \"))\n",
+    "\n",
+    "inventory[\"t-shirt\"] = cantidad_tshirt\n",
+    "inventory[\"mug\"] = cantidad_mug\n",
+    "inventory[\"hat\"] = cantidad_hat\n",
+    "inventory[\"book\"] = cantidad_book\n",
+    "inventory[\"keychain\"] = cantidad_keychain\n",
+    "\n",
+    "# Paso 4\n",
+    "customer_orders = set()\n",
+    "\n",
+    "# Paso 5\n",
+    "producto1 = input(\"Introduce el primer producto que desea pedir: \")\n",
+    "producto2 = input(\"Introduce el segundo producto que desea pedir: \")\n",
+    "producto3 = input(\"Introduce el tercer producto que desea pedir: \")\n",
+    "\n",
+    "customer_orders.add(producto1)\n",
+    "customer_orders.add(producto2)\n",
+    "customer_orders.add(producto3)\n",
+    "\n",
+    "# Paso 6\n",
+    "print(\"Productos pedidos:\")\n",
+    "for producto in customer_orders:\n",
+    "    print(producto)\n",
+    "\n",
+    "# Paso 7: Calcular las estadísticas del pedido\n",
+    "total_products_ordered = len(customer_orders)          # Total de productos pedidos\n",
+    "total_available_products = len(products)               # Total de productos disponibles\n",
+    "percentage_ordered = (total_products_ordered / total_available_products) * 100\n",
+    "order_status = (total_products_ordered, percentage_ordered)  # Tupla con las estadísticas\n",
+    "\n",
+    "# Paso 8\n",
+    "print(\"Order Statistics:\")\n",
+    "print(f\"Total Products Ordered: {order_status[0]}\")\n",
+    "print(f\"Percentage of Products Ordered: {order_status[1]:.2f}%\")\n",
+    "\n",
+    "# Paso 9\n",
+    "if \"t-shirt\" in customer_orders:\n",
+    "    inventory[\"t-shirt\"] -= 1\n",
+    "if \"mug\" in customer_orders:\n",
+    "    inventory[\"mug\"] -= 1\n",
+    "if \"hat\" in customer_orders:\n",
+    "    inventory[\"hat\"] -= 1\n",
+    "if \"book\" in customer_orders:\n",
+    "    inventory[\"book\"] -= 1\n",
+    "if \"keychain\" in customer_orders:\n",
+    "    inventory[\"keychain\"] -= 1\n",
+    "\n",
+    "# Paso 10\n",
+    "print(\"Inventario actualizado:\")\n",
+    "print(\"t-shirt:\", inventory[\"t-shirt\"])\n",
+    "print(\"mug:\", inventory[\"mug\"])\n",
+    "print(\"hat:\", inventory[\"hat\"])\n",
+    "print(\"book:\", inventory[\"book\"])\n",
+    "print(\"keychain:\", inventory[\"keychain\"])"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -68,7 +164,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.14.4"
   }
  },
  "nbformat": 4,