ejercicios data structures

lab-python-data-structures.ipynb

@@ -50,11 +50,198 @@
     "\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": 87,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#1\n",
+    "\n",
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#2\n",
+    "\n",
+    "inventory = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 4, 'mug': 3, 'hat': 2}"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#3\n",
+    "\n",
+    "input1 = int(input(f\"Enter a quantity of t-shirt: {products} \"))\n",
+    "input2 = int(input(f\"Enter a quantity of mug: {products}\"))\n",
+    "input3 = int(input(f\"Enter a quantity of hats: {products}\"))\n",
+    "\n",
+    "inventory[\"t-shirt\"] = input1\n",
+    "inventory[\"mug\"] = input2\n",
+    "inventory[\"hat\"] = input3\n",
+    "\n",
+    "\n",
+    "inventory\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#4\n",
+    "\n",
+    "customer_orders = set()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#5\n",
+    "\n",
+    "input4 = input(f\"Dime que producto quieres: {products}\")\n",
+    "input5 = input(f\"Dime que producto quieres: {products}\")\n",
+    "input6 = input(f\"Dime que producto quieres: {products}\")\n",
+    "\n",
+    "customer_orders.add(input4)\n",
+    "customer_orders.add(input5)\n",
+    "customer_orders.add(input6)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'mug', 'hat', 't-shirt', 'book'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "#6\n",
+    "\n",
+    "print(customer_orders)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "60.0"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#7\n",
+    "\n",
+    "total_products_ordered= len(customer_orders)\n",
+    "total_products_ordered\n",
+    "\n",
+    "percentage_ordered = (total_products_ordered / len(products)) * 100\n",
+    "percentage_ordered\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "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",
+    "\n",
+    "print(\"Order Statistics:\" \\\n",
+    "\"\\nTotal Products Ordered:\", total_products_ordered, \\\n",
+    "\"\\nPercentage of Products Ordered:\", percentage_ordered, \"%\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#9\n",
+    "inventory\n",
+    "\n",
+    "inventory[products[0]]  = inventory[products[0]] - 1\n",
+    "inventory[products[1]] = inventory[products[1]] - 1\n",
+    "inventory[products[2]] = inventory[products[2]] - 1\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 2, 'mug': 1, 'hat': 0}"
+      ]
+     },
+     "execution_count": 95,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#10\n",
+    "\n",
+    "inventory"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "base",
    "language": "python",
    "name": "python3"
   },
@@ -68,7 +255,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,