diff --git a/lab-python-data-structures.ipynb b/lab-python-data-structures.ipynb
index 5b3ce9e0..d9e47949 100644
--- a/lab-python-data-structures.ipynb
+++ b/lab-python-data-structures.ipynb
@@ -50,13 +50,85 @@
     "\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": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Please enter stock for article t-shirt 1\n",
+      "Please enter stock for article mug 2\n",
+      "Please enter stock for article hat 3\n",
+      "Please enter stock for article book 4\n",
+      "Please enter stock for article keychain 5\n",
+      "Please enter 0 for t-shirt, 1 for mug, 2 for hat, 3 for book or 4 for keychain 1\n",
+      "Please enter 0 for t-shirt, 1 for mug, 2 for hat, 3 for book or 4 for keychain 2\n",
+      "Please enter 0 for t-shirt, 1 for mug, 2 for hat, 3 for book or 4 for keychain 3\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'mug', 'hat', 'book'}\n",
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Products Ordered: 60.0 %\n",
+      "The stock for t-shirt is 1\n",
+      "The stock for mug is 1\n",
+      "The stock for hat is 2\n",
+      "The stock for book is 3\n",
+      "The stock for keychain is 5\n"
+     ]
+    }
+   ],
+   "source": [
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "\n",
+    "inventory = {}\n",
+    "\n",
+    "for product in products:\n",
+    "    stock = int(input(f\"Please enter stock for article {product}\"))\n",
+    "    inventory[product] = stock\n",
+    "\n",
+    "customer_orders = set()\n",
+    "\n",
+    "for purchase in range(3):\n",
+    "    customer_orders.add(products[int(input(\"Please enter 0 for t-shirt, 1 for mug, 2 for hat, 3 for book or 4 for keychain\"))])\n",
+    "\n",
+    "print(customer_orders)\n",
+    "\n",
+    "total_products_ordered = len(customer_orders)\n",
+    "percentage_ordered = (len(customer_orders)/len(inventory.values()))*100\n",
+    "\n",
+    "print(f\"\"\"Order Statistics:\n",
+    "Total Products Ordered: {total_products_ordered}\n",
+    "Percentage of Products Ordered: {percentage_ordered} %\"\"\")\n",
+    "\n",
+    "for product in customer_orders:\n",
+    "    inventory[product] -= 1\n",
+    "\n",
+    "for product in products:\n",
+    "    print(\"The stock for\", product, \"is\", inventory[product])\n"
+   ]
+  },
+  {
+   "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 +140,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,