diff --git a/lab-python-functions.ipynb b/lab-python-functions.ipynb
index 44d337b..5ea1246 100644
--- a/lab-python-functions.ipynb
+++ b/lab-python-functions.ipynb
@@ -43,13 +43,210 @@
     "\n",
     "\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "bc83c382-69fd-4127-90ae-acac2340992c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "7e2a1b8e-7104-4039-ab93-1c3e2c50db6b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter quantity available for: t-shirt 3\n",
+      "Enter quantity available for: mug 4\n",
+      "Enter quantity available for: hat 5\n",
+      "Enter quantity available for: book 6\n",
+      "Enter quantity available for: keychain 7\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'t-shirt': 3, 'mug': 4, 'hat': 5, 'book': 6, 'keychain': 7}\n"
+     ]
+    }
+   ],
+   "source": [
+    "def initialize_inventory(products):\n",
+    "    inventory = {}\n",
+    "\n",
+    "    for product in products:\n",
+    "        quantity = int(input(f\"Enter quantity available for: {product}\"))\n",
+    "        inventory[product] = quantity \n",
+    "\n",
+    "    return inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "bd673586-0367-4aa9-b958-6b8d93067487",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_customer_orders():\n",
+    "    customer_orders = set()\n",
+    "\n",
+    "    while True:\n",
+    "        order = input(\"Enter a product: \")\n",
+    "        customer_orders.add(order)\n",
+    "\n",
+    "        another = input(\"Do you want to add another product? (yes/no): \")\n",
+    "        if another != \"yes\":\n",
+    "            break\n",
+    "\n",
+    "    return customer_orders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "0a583cd6-c774-4c80-ac40-6009cf812385",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def update_inventory(customer_orders, inventory):\n",
+    "    for product in customer_orders:\n",
+    "        inventory[product] = inventory[product] - 1\n",
+    "        \n",
+    "    \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "ea37dc2d-896c-4bb3-8884-8b32346f13f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def calculate_order_statistics(customer_orders, products): \n",
+    "    total_orders = len(customer_orders)\n",
+    "    percentage_of_orders = len(customer_orders)/len(products)\n",
+    "\n",
+    "    return total_orders, percentage_of_orders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "ad73879f-5acc-4d11-903f-fe4c96b272aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_order_statistics(order_statistics): \n",
+    "    print(\"Order statistics:\")\n",
+    "    print(f\"Total products ordered: {total_orders}\")\n",
+    "    print(f\"Percentage of unique products: {percentage_of_orders}\")\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "25a8197b-e9de-4f09-ad51-457946f6b1cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter quantity available for: t-shirt 4\n",
+      "Enter quantity available for: mug 4\n",
+      "Enter quantity available for: hat 4\n",
+      "Enter quantity available for: book 4\n",
+      "Enter quantity available for: keychain 4\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 4, 'mug': 4, 'hat': 4, 'book': 4, 'keychain': 4}"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initialize_inventory(products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "001ed7df-b37c-4c47-b8d2-5d02d74ab101",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter a product:  mug\n",
+      "Do you want to add another product? (yes/no):  yes\n",
+      "Enter a product:  hat\n",
+      "Do you want to add another product? (yes/no):  no\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'hat', 'mug'}"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "get_customer_orders()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "590f6518-504b-4a4f-81b0-9a934261ce36",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "None\n"
+     ]
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6acd0200-b879-443e-9f93-59322d62340e",
+   "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": {
@@ -61,7 +258,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.9"
   }
  },
  "nbformat": 4,