diff --git a/.ipynb_checkpoints/lab-python-functions-checkpoint.ipynb b/.ipynb_checkpoints/lab-python-functions-checkpoint.ipynb
new file mode 100644
index 0000000..1e7c4f8
--- /dev/null
+++ b/.ipynb_checkpoints/lab-python-functions-checkpoint.ipynb
@@ -0,0 +1,342 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "67c29ba6-5fe5-4d4a-8eb2-fc62adbfc9e8",
+   "metadata": {},
+   "source": [
+    "# Lab | Functions"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "3a984506-2423-4320-939b-88a1b048d220",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Exercise: Managing Customer Orders with Functions\n",
+    "\n",
+    "In the previous exercise, you improved the code for managing customer orders by using loops and flow control. Now, let's take it a step further and refactor the code by introducing functions.\n",
+    "\n",
+    "Follow the steps below to complete the exercise:\n",
+    "\n",
+    "1. Define a function named `initialize_inventory` that takes `products` as a parameter. Inside the function, implement the code for initializing the inventory dictionary using a loop and user input.\n",
+    "\n",
+    "2. Define a function named `get_customer_orders` that takes no parameters. Inside the function, implement the code for prompting the user to enter the product names using a loop. The function should return the `customer_orders` set.\n",
+    "\n",
+    "3. Define a function named `update_inventory` that takes `customer_orders` and `inventory` as parameters. Inside the function, implement the code for updating the inventory dictionary based on the customer orders.\n",
+    "\n",
+    "4. Define a function named `calculate_order_statistics` that takes `customer_orders` and `products` as parameters. Inside the function, implement the code for calculating the order statistics (total products ordered, and percentage of unique products ordered). The function should return these values.\n",
+    "\n",
+    "5. Define a function named `print_order_statistics` that takes `order_statistics` as a parameter. Inside the function, implement the code for printing the order statistics.\n",
+    "\n",
+    "6. Define a function named `print_updated_inventory` that takes `inventory` as a parameter. Inside the function, implement the code for printing the updated inventory.\n",
+    "\n",
+    "7. Call the functions in the appropriate sequence to execute the program and manage customer orders.\n",
+    "\n",
+    "Hints for functions:\n",
+    "\n",
+    "- Consider the input parameters required for each function and their return values.\n",
+    "- Utilize function parameters and return values to transfer data between functions.\n",
+    "- Test your functions individually to ensure they work correctly.\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e60a44f1-5b97-4e0c-923e-504790a7bf25",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#1.\n",
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "def initialize_inventory(products):\n",
+    "    global inventory\n",
+    "    inventory = {}\n",
+    "    for product in products:\n",
+    "        quantity = int(input(f\"please input the quantity of {product}\"))\n",
+    "        inventory[product]= quantity\n",
+    "    return inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "27908571-eb2b-46a1-884b-270f1f6d2808",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "please input the quantity of t-shirt 55\n",
+      "please input the quantity of mug 244\n",
+      "please input the quantity of hat 25\n",
+      "please input the quantity of book 78\n",
+      "please input the quantity of keychain 33\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 55, 'mug': 244, 'hat': 25, 'book': 78, 'keychain': 33}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initialize_inventory(products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "46dd1902-7747-46c1-8899-42bd65f02b19",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#2 \n",
+    "customer_orders = set()\n",
+    "def get_customer_orders():\n",
+    "    answer=input(\"do you want to add another product? yes or no\")\n",
+    "    while answer==\"yes\":\n",
+    "        order=input(\"product the customer wants to order\")\n",
+    "        answer=input(\"do you want to add another product? yes or no\")\n",
+    "        if order in products:\n",
+    "            customer_orders.add(order)\n",
+    "    return customer_orders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "bdf34740-9b75-42af-929c-3125f7a01026",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "do you want to add another product? yes or no yes\n",
+      "product the customer wants to order hat\n",
+      "do you want to add another product? yes or no yes\n",
+      "product the customer wants to order mug\n",
+      "do you want to add another product? yes or no no\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'hat', 'mug'}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "get_customer_orders()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b4d19da9-2802-4722-8d03-18fc92e1a053",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#3\n",
+    "def update_inventory(customer_orders, inventory):\n",
+    "    for products in inventory:\n",
+    "        if products in customer_orders:\n",
+    "            inventory[products] = inventory[products]-1\n",
+    "    return inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "c1e86ca1-8692-4ffe-89fc-81d0fb1b4cea",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 55, 'mug': 241, 'hat': 22, 'book': 78, 'keychain': 33}"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "update_inventory(customer_orders, inventory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "03b7bdfd-2bbb-4284-b547-528d4e565ff4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 55, 'mug': 242, 'hat': 23, 'book': 78, 'keychain': 33}"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "b938ea5c-e5cc-40b6-91a2-d6f085bccc16",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#4\n",
+    "def calculate_order_statistics(customer_orders, products):\n",
+    "    total_products_ordered = len(customer_orders)\n",
+    "    percentage_unique_ordered = total_products_ordered / sum(inventory.values())\n",
+    "    return total_products_ordered, percentage_unique_ordered"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "c7d7c58d-8dbb-4f69-9d7d-71c2e62fe714",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2, 0.004662004662004662)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "calculate_order_statistics(customer_orders, products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "f5459923-9357-47a0-96cc-abff937a5741",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "order_statistics = calculate_order_statistics(customer_orders, products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "480ea4df-bb6c-4c2a-9b1e-357e37954353",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#5\n",
+    "def print_order_statistics(order_statistics):\n",
+    "    print (calculate_order_statistics(customer_orders, products))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "05fc13d3-a3ec-41c1-8b20-8a141879384b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2, 0.004662004662004662)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_order_statistics(order_statistics)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "8ae3257d-f6d9-45a3-94d1-436a89993395",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#5\n",
+    "def print_updated_inventory(inventory):\n",
+    "    print(update_inventory(customer_orders, inventory))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "030b91bd-7fc9-42d5-9bae-85c248e7006c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'t-shirt': 55, 'mug': 240, 'hat': 21, 'book': 78, 'keychain': 33}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_updated_inventory(inventory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b143c5ad-4314-4919-a370-5ed7c3081e3f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:base] *",
+   "language": "python",
+   "name": "conda-base-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/lab-python-functions.ipynb b/lab-python-functions.ipynb
index 44d337b..d9d3284 100644
--- a/lab-python-functions.ipynb
+++ b/lab-python-functions.ipynb
@@ -1,16 +1,16 @@
 {
  "cells": [
   {
-   "cell_type": "markdown",
-   "id": "25d7736c-ba17-4aff-b6bb-66eba20fbf4e",
+   "cell_type": "raw",
+   "id": "67c29ba6-5fe5-4d4a-8eb2-fc62adbfc9e8",
    "metadata": {},
    "source": [
     "# Lab | Functions"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "0c581062-8967-4d93-b06e-62833222f930",
+   "cell_type": "raw",
+   "id": "3a984506-2423-4320-939b-88a1b048d220",
    "metadata": {
     "tags": []
    },
@@ -43,13 +43,332 @@
     "\n",
     "\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e60a44f1-5b97-4e0c-923e-504790a7bf25",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#1.\n",
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "def initialize_inventory(products):\n",
+    "    global inventory\n",
+    "    inventory = {}\n",
+    "    for product in products:\n",
+    "        quantity = int(input(f\"please input the quantity of {product}\"))\n",
+    "        inventory[product]= quantity\n",
+    "    return inventory"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "141a322d-635d-48cb-a2cb-63e2ed9b3726",
+   "metadata": {},
+   "source": [
+    "#1\n",
+    "\n",
+    "def initialize_inventory(products):\n",
+    "inventory = {}\n",
+    "for product in products:\n",
+    "quantitiy = int(input(f\"please input the quantity of {product}\"))\n",
+    "inventory(product) = quantity #adding a key value pair to the dictionary called inventory. It stores the quantity input for the given key\n",
+    "return inventory\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc51c863-b0d7-47d5-a0b3-1f339443e6cb",
+   "metadata": {},
+   "source": [
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "inventory = initialize_inventory(products) #call for the function and save result in inventory\n",
+    "print(inventory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "27908571-eb2b-46a1-884b-270f1f6d2808",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "please input the quantity of t-shirt 55\n",
+      "please input the quantity of mug 244\n",
+      "please input the quantity of hat 25\n",
+      "please input the quantity of book 78\n",
+      "please input the quantity of keychain 33\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 55, 'mug': 244, 'hat': 25, 'book': 78, 'keychain': 33}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initialize_inventory(products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "46dd1902-7747-46c1-8899-42bd65f02b19",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#2 \n",
+    "customer_orders = set()\n",
+    "def get_customer_orders():\n",
+    "    answer=input(\"do you want to add another product? yes or no\")\n",
+    "    while answer==\"yes\":\n",
+    "        order=input(\"product the customer wants to order\")\n",
+    "        answer=input(\"do you want to add another product? yes or no\")\n",
+    "        if order in products:\n",
+    "            customer_orders.add(order)\n",
+    "    return customer_orders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8bfd43ad-d323-4a17-b63f-764d0e27aedc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "bdf34740-9b75-42af-929c-3125f7a01026",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "do you want to add another product? yes or no yes\n",
+      "product the customer wants to order hat\n",
+      "do you want to add another product? yes or no yes\n",
+      "product the customer wants to order mug\n",
+      "do you want to add another product? yes or no no\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'hat', 'mug'}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "get_customer_orders()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b4d19da9-2802-4722-8d03-18fc92e1a053",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#3\n",
+    "def update_inventory(customer_orders, inventory):\n",
+    "    for products in inventory:\n",
+    "        if products in customer_orders:\n",
+    "            inventory[products] = inventory[products]-1\n",
+    "    return inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "c1e86ca1-8692-4ffe-89fc-81d0fb1b4cea",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 55, 'mug': 241, 'hat': 22, 'book': 78, 'keychain': 33}"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "update_inventory(customer_orders, inventory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "03b7bdfd-2bbb-4284-b547-528d4e565ff4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 55, 'mug': 242, 'hat': 23, 'book': 78, 'keychain': 33}"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "inventory"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8014509-5a31-44c1-b12a-e7f2774043cc",
+   "metadata": {},
+   "source": [
+    "#3\n",
+    "def update_inventory(customer_orders, inventory):\n",
+    "for product, quantity in customer_orders.items():\n",
+    "if product in inventrory:\n",
+    "inventory(product) -= customer_orders[product]\n",
+    "return inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "b938ea5c-e5cc-40b6-91a2-d6f085bccc16",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#4\n",
+    "def calculate_order_statistics(customer_orders, products):\n",
+    "    total_products_ordered = len(customer_orders)\n",
+    "    percentage_unique_ordered = total_products_ordered / sum(inventory.values())\n",
+    "    return total_products_ordered, percentage_unique_ordered"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "c7d7c58d-8dbb-4f69-9d7d-71c2e62fe714",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2, 0.004662004662004662)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "calculate_order_statistics(customer_orders, products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "f5459923-9357-47a0-96cc-abff937a5741",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "order_statistics = calculate_order_statistics(customer_orders, products)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "480ea4df-bb6c-4c2a-9b1e-357e37954353",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#5\n",
+    "def print_order_statistics(order_statistics):\n",
+    "    print (calculate_order_statistics(customer_orders, products))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "05fc13d3-a3ec-41c1-8b20-8a141879384b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2, 0.004662004662004662)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_order_statistics(order_statistics)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "8ae3257d-f6d9-45a3-94d1-436a89993395",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#5\n",
+    "def print_updated_inventory(inventory):\n",
+    "    print(update_inventory(customer_orders, inventory))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "030b91bd-7fc9-42d5-9bae-85c248e7006c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'t-shirt': 55, 'mug': 240, 'hat': 21, 'book': 78, 'keychain': 33}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_updated_inventory(inventory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b143c5ad-4314-4919-a370-5ed7c3081e3f",
+   "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 +380,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,