diff --git a/lab-python-list-comprehension.ipynb b/lab-python-list-comprehension.ipynb
index 5a3c3e1..283b90c 100644
--- a/lab-python-list-comprehension.ipynb
+++ b/lab-python-list-comprehension.ipynb
@@ -75,11 +75,138 @@
     "\n",
     "```\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "dc7160d9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Unique Products Ordered: 60.0\n",
+      "\n",
+      "Updated Inventory:\n",
+      "t-shirt: 4\n",
+      "mug: 3\n",
+      "hat: 4\n",
+      "book: 5\n",
+      "keychain: 3\n",
+      "Total Price: 45.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "def initialize_inventory(products):\n",
+    "    \"\"\"\n",
+    "    Build the inventory dict using a dict comprehension + user input.\n",
+    "    Example input prompt: \"Enter the quantity of t-shirts available:  \"\n",
+    "    \"\"\"\n",
+    "    return {\n",
+    "        product: int(input(f\"Enter the quantity of {product}s available:  \"))\n",
+    "        for product in products\n",
+    "    }\n",
+    "\n",
+    "\n",
+    "def get_customer_orders():\n",
+    "    \"\"\"\n",
+    "    Ask how many orders to take, then gather product names.\n",
+    "    Uses a set comprehension so duplicates collapse automatically.\n",
+    "    \"\"\"\n",
+    "    n = int(input(\"Enter the number of customer orders:  \"))\n",
+    "    return {\n",
+    "        input(\"Enter the name of a product that a customer wants to order:  \").strip().lower()\n",
+    "        for _ in range(n)\n",
+    "    }\n",
+    "\n",
+    "\n",
+    "def update_inventory(customer_orders, inventory):\n",
+    "    \"\"\"\n",
+    "    Deduct one unit (at most 1 per product) for each ordered item that exists and has stock.\n",
+    "    Then remove zero-quantity products using a dict comprehension.\n",
+    "    Returns the updated (filtered) inventory.\n",
+    "    \"\"\"\n",
+    "    for item in customer_orders:\n",
+    "        if item in inventory and inventory[item] > 0:\n",
+    "            inventory[item] -= 1\n",
+    "\n",
+    "    # Filter out zero-quantity items via dict comprehension\n",
+    "    inventory = {k: v for k, v in inventory.items() if v > 0}\n",
+    "    return inventory\n",
+    "\n",
+    "\n",
+    "def calculate_order_statistics(customer_orders, products):\n",
+    "    \"\"\"\n",
+    "    Compute total unique products ordered and percentage vs catalog size.\n",
+    "    \"\"\"\n",
+    "    total_unique = len(customer_orders)\n",
+    "    percent_unique = (total_unique / len(products) * 100) if products else 0.0\n",
+    "    return total_unique, percent_unique\n",
+    "\n",
+    "\n",
+    "def print_order_statistics(order_statistics):\n",
+    "    total_unique, percent_unique = order_statistics\n",
+    "    print(\"\\nOrder Statistics:\")\n",
+    "    print(f\"Total Products Ordered: {total_unique}\")\n",
+    "    print(f\"Percentage of Unique Products Ordered: {percent_unique:.1f}\")\n",
+    "\n",
+    "\n",
+    "def print_updated_inventory(inventory):\n",
+    "    \"\"\"\n",
+    "    Print the inventory in a compact way using a generator expression.\n",
+    "    \"\"\"\n",
+    "    print(\"\\nUpdated Inventory:\")\n",
+    "    if not inventory:\n",
+    "        print(\"(All items are out of stock.)\")\n",
+    "        return\n",
+    "    print(\"\\n\".join(f\"{k}: {v}\" for k, v in inventory.items()))\n",
+    "\n",
+    "\n",
+    "def calculate_total_price(customer_orders):\n",
+    "    \"\"\"\n",
+    "    Prompt for the price of each ordered product and sum them.\n",
+    "    Uses a dict comprehension to capture per-item prices (optional to reuse),\n",
+    "    then sums values with a generator expression.\n",
+    "    Assumes 1 unit per product.\n",
+    "    \"\"\"\n",
+    "    prices = {item: float(input(f\"Enter the price of {item}:  \")) for item in customer_orders}\n",
+    "    total = sum(prices.values())\n",
+    "    return total\n",
+    "\n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "\n",
+    "    inventory = initialize_inventory(products)\n",
+    "    customer_orders = get_customer_orders()\n",
+    "\n",
+    "    stats = calculate_order_statistics(customer_orders, products)\n",
+    "    print_order_statistics(stats)\n",
+    "\n",
+    "    inventory = update_inventory(customer_orders, inventory)\n",
+    "    print_updated_inventory(inventory)\n",
+    "\n",
+    "    total_price = calculate_total_price(customer_orders)\n",
+    "    print(f\"Total Price: {total_price:.1f}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6e1344ff",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -93,7 +220,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.9.6"
   }
  },
  "nbformat": 4,