diff --git a/lab-python-functions.ipynb b/lab-python-functions.ipynb
index 44d337b..7a970ef 100644
--- a/lab-python-functions.ipynb
+++ b/lab-python-functions.ipynb
@@ -43,13 +43,223 @@
     "\n",
     "\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "aaf1c5c1-a090-4987-b099-5fefc888a40c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def initialize_inventory (products):\n",
+    "    inventory={}\n",
+    "    for item in products:\n",
+    "        inventory[item]=int(input(f\"quantity of {item} available in the inventory: \"))\n",
+    "    \n",
+    "    return inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2fe60b8a-cab8-4836-b19f-6f7811294dc5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_customer_orders():\n",
+    "    customer_orders=set() \n",
+    "    add_another_product=\"yes\"\n",
+    "    \n",
+    "    while add_another_product== \"yes\" :\n",
+    "        x=input(\"input order :\")\n",
+    "        customer_orders.add(x)\n",
+    "        add_another_product=input(\"if you want to add another product (yes/no):\")\n",
+    "    \n",
+    "    return customer_orders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "05ac0ed1-3263-4ca4-878e-fb87ddf8e218",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def update_inventory (customer_orders, inventory ):\n",
+    "    for item in customer_orders:\n",
+    "     inventory[item]=inventory[item]-1\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "4e6d5357-6e82-4f44-b1b5-f1ab6e9838ac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def calculate_order_statistics (customer_orders, products):\n",
+    "    total_products_ordered=len(customer_orders)\n",
+    "    percentage_ordered=len(customer_orders)/len(products)*100\n",
+    "    order_statistics=(total_products_ordered,percentage_ordered)\n",
+    "    return order_statistics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "75fdd038-5d04-4ab9-b2ce-7c125c642161",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_order_statistics (order_statistics ):\n",
+    "    print(\"Order Statistics:\")\n",
+    "    print(f\"Total Products Ordered:{order_statistics[0] }\")\n",
+    "    print(f\"Percentage of Products Ordered:{order_statistics[1]}\")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "bbea8abd-b8eb-4765-9cd2-4ef7384b31fb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_updated_inventory(inventory ):\n",
+    "    print (inventory)\n",
+    "    print(inventory.items())\n",
+    "    print(inventory.keys())\n",
+    "    print(inventory.values())\n",
+    "    for item in inventory.items() :\n",
+    "      print(item)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a35ff804-b525-4aee-b161-fd93bf55a282",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "quantity of t-shirt available in the inventory:  20\n",
+      "quantity of mug available in the inventory:  34\n",
+      "quantity of hat available in the inventory:  46\n",
+      "quantity of book available in the inventory:  52\n",
+      "quantity of keychain available in the inventory:  63\n"
+     ]
+    }
+   ],
+   "source": [
+    "products=[\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "inventory=initialize_inventory (products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7afd25dc-b382-4d4f-901a-f78a77c906cb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "input order : mug\n",
+      "if you want to add another product (yes/no): yes\n",
+      "input order : hat\n",
+      "if you want to add another product (yes/no): no\n"
+     ]
+    }
+   ],
+   "source": [
+    "customer_orders=get_customer_orders()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "752eff20-64f9-42a1-ad78-ae657464d5b8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "update_inventory (customer_orders, inventory )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6ac4887d-25d8-4960-8c27-4c663f4fb39e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "order_status=calculate_order_statistics (customer_orders, products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "df70ee9b-4071-44ec-b7f8-fee1b32bb101",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Order Statistics:\n",
+      "Total Products Ordered:2\n",
+      "Percentage of Products Ordered:40.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_order_statistics (order_status)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "34e7ad70-a217-41c5-abba-079db6368835",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'t-shirt': 20, 'mug': 32, 'hat': 44, 'book': 52, 'keychain': 63}\n",
+      "dict_items([('t-shirt', 20), ('mug', 32), ('hat', 44), ('book', 52), ('keychain', 63)])\n",
+      "dict_keys(['t-shirt', 'mug', 'hat', 'book', 'keychain'])\n",
+      "dict_values([20, 32, 44, 52, 63])\n",
+      "('t-shirt', 20)\n",
+      "('mug', 32)\n",
+      "('hat', 44)\n",
+      "('book', 52)\n",
+      "('keychain', 63)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_updated_inventory(inventory )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8f9e85e1-1599-4df2-8550-2f84797c3d39",
+   "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 +271,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.9"
   }
  },
  "nbformat": 4,