diff --git a/lab-python-data-structures.ipynb b/lab-python-data-structures.ipynb
index 5b3ce9e0..646e7e22 100644
--- a/lab-python-data-structures.ipynb
+++ b/lab-python-data-structures.ipynb
@@ -34,7 +34,7 @@
     "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.\n",
-    "   \n",
+    " percentage_ordered  \n",
     "   Store these statistics in a tuple called `order_status`.\n",
     "\n",
     "8. Print the order statistics using the following format:\n",
@@ -50,13 +50,299 @@
     "\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": [
+    "products=[\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inventory={}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "quantity of t-shirt available in the inventory:  22\n"
+     ]
+    }
+   ],
+   "source": [
+    "inventory[\"t-shirt\"]=int(input(\"quantity of t-shirt available in the inventory: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "quantity of mug available in the inventory:  32\n"
+     ]
+    }
+   ],
+   "source": [
+    "inventory[\"mug\"]=int(input(\"quantity of mug available in the inventory: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "quantity of hat available in the inventory:  45\n"
+     ]
+    }
+   ],
+   "source": [
+    "inventory[\"hat\"]=int(input(\"quantity of hat available in the inventory: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "quantity of book available in the inventory:  56\n"
+     ]
+    }
+   ],
+   "source": [
+    "inventory[\"book\"]=int(input(\"quantity of book available in the inventory: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "quantity of keychain available in the inventory:  72\n"
+     ]
+    }
+   ],
+   "source": [
+    "inventory[\"keychain\"]=int(input(\"quantity of keychain available in the inventory: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "customer_orders=set() \n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "input order1:  mug\n",
+      "input order2:  hat\n",
+      "input order3:  book\n"
+     ]
+    }
+   ],
+   "source": [
+    "x=input(\"input order1: \")\n",
+    "y=input(\"input order2: \")\n",
+    "z=input(\"input order3: \")\n",
+    "customer_orders.add(x)\n",
+    "customer_orders.add(y)\n",
+    "customer_orders.add(z)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'book', 'hat', 'mug'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(customer_orders)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3\n"
+     ]
+    }
+   ],
+   "source": [
+    "total_products_ordered=len(customer_orders)\n",
+    "print(total_products_ordered)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "percentage_ordered=len(customer_orders)/len(products)*100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "order_status=(total_products_ordered,percentage_ordered)"
+   ]
+  },
+  {
+   "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": [
+    "print(\"Order Statistics:\")\n",
+    "print(\"Total Products Ordered: \"+ str(total_products_ordered))\n",
+    "print(\"Percentage of Products Ordered: \"+ str(percentage_ordered))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for item in customer_orders:\n",
+    "    inventory[item]=inventory[item]-1\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'t-shirt': 22, 'mug': 31, 'hat': 44, 'book': 55, 'keychain': 72}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print (inventory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "('t-shirt', 22)\n",
+      "('mug', 31)\n",
+      "('hat', 44)\n",
+      "('book', 55)\n",
+      "('keychain', 72)\n"
+     ]
+    }
+   ],
+   "source": [
+    "for item in inventory.items() :\n",
+    "    print(item)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dict_items([('t-shirt', 22), ('mug', 31), ('hat', 44), ('book', 55), ('keychain', 72)])\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(inventory.items())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python [conda env:base] *",
    "language": "python",
-   "name": "python3"
+   "name": "conda-base-py"
   },
   "language_info": {
    "codemirror_mode": {
@@ -68,7 +354,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.9"
   }
  },
  "nbformat": 4,