diff --git a/lab-python-data-structures.ipynb b/lab-python-data-structures.ipynb
index 5b3ce9e0..07b6a4ae 100644
--- a/lab-python-data-structures.ipynb
+++ b/lab-python-data-structures.ipynb
@@ -50,11 +50,212 @@
     "\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": [
+    {
+     "data": {
+      "text/plain": [
+       "['t-shirts', 'mug', 'hat', 'book', 'keychain']"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "products=[\"t-shirt\",\"mug\",\"hat\",\"book\",\"keychain\"]\n",
+    "products"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inventory={}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inventory[\"t-shirt\"]=int(input(\"enter the quantity of t-shirt\"))\n",
+    "inventory[\"mug\"]=int(input(\"enter the quantity of mug\"))\n",
+    "inventory[\"hat\"]=int(input(\"enter the quantity of hat\"))\n",
+    "inventory[\"book\"]=int(input(\"enter the quantity of book\"))\n",
+    "inventory[\"keychain\"]=int(input(\"enter the quantity of keychain\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "customer_orders=set()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "order1=input(\"enter your order\")\n",
+    "order2=input(\"enter your order\")\n",
+    "order3=input(\"enter your order\")\n",
+    "if order1 in products:\n",
+    "    customer_orders.add(order1)\n",
+    "else:\n",
+    "    print(\"order1 not found\")\n",
+    "if order2 in products:\n",
+    "    customer_orders.add(order2)\n",
+    "else:\n",
+    "    print(\"order2 not found\")\n",
+    "if order3 in products:\n",
+    "    customer_orders.add(order3)\n",
+    "else:\n",
+    "    print(\"order3 not found\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'hat', 'mug', 'book'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(customer_orders)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3\n",
+      "60.0\n",
+      "(3, 60.0)\n"
+     ]
+    }
+   ],
+   "source": [
+    "total_products_order=len(customer_orders)\n",
+    "print(total_products_order)\n",
+    "percentage_ordered=(total_products_order / len(products)) * 100\n",
+    "print(percentage_ordered)\n",
+    "order_status=(total_products_order,percentage_ordered)\n",
+    "print(order_status)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Products Ordered: 60.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "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": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirts': 9, 'mug': 19, 'hat': 29, 'book': 39, 'keychain': 49}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "inventory[\"t-shirt\"] -=1\n",
+    "inventory[\"mug\"] -=1\n",
+    "inventory[\"hat\"] -=1\n",
+    "inventory[\"book\"] -=1\n",
+    "inventory[\"keychain\"] -=1\n",
+    "inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t-shirts: 9\n",
+      "mug: 19\n",
+      "hat: 29\n",
+      "book: 39\n",
+      "keychain: 49\n"
+     ]
+    }
+   ],
+   "source": [
+    "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\"] )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -68,7 +269,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,