diff --git a/.ipynb_checkpoints/lab-python-data-structures-checkpoint.ipynb b/.ipynb_checkpoints/lab-python-data-structures-checkpoint.ipynb
new file mode 100644
index 00000000..1791fb57
--- /dev/null
+++ b/.ipynb_checkpoints/lab-python-data-structures-checkpoint.ipynb
@@ -0,0 +1,256 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# Lab | Data Structures "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercise: Managing Customer Orders\n",
+    "\n",
+    "As part of a business venture, you are starting an online store that sells various products. To ensure smooth operations, you need to develop a program that manages customer orders and inventory.\n",
+    "\n",
+    "Follow the steps below to complete the exercise:\n",
+    "\n",
+    "1. Define a list called `products` that contains the following items: \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\".\n",
+    "\n",
+    "2. Create an empty dictionary called `inventory`.\n",
+    "\n",
+    "3. Ask the user to input the quantity of each product available in the inventory. Use the product names from the `products` list as keys in the `inventory` dictionary and assign the respective quantities as values.\n",
+    "\n",
+    "4. Create an empty set called `customer_orders`.\n",
+    "\n",
+    "5. Ask the user to input the name of three products that a customer wants to order (from those in the products list, meaning three products out of \"t-shirt\", \"mug\", \"hat\", \"book\" or \"keychain\". Add each product name to the `customer_orders` set.\n",
+    "\n",
+    "6. Print the products in the `customer_orders` set.\n",
+    "\n",
+    "7. Calculate the following order statistics:\n",
+    "   - Total Products Ordered: The total number of products in the `customer_orders` set.\n",
+    "   - Percentage of Products Ordered: The percentage of products ordered compared to the total available products.\n",
+    "   \n",
+    "   Store these statistics in a tuple called `order_status`.\n",
+    "\n",
+    "8. Print the order statistics using the following format:\n",
+    "   ```\n",
+    "   Order Statistics:\n",
+    "   Total Products Ordered: <total_products_ordered>\n",
+    "   Percentage of Products Ordered: <percentage_ordered>% \n",
+    "   ```\n",
+    "\n",
+    "9. Update the inventory by subtracting 1 from the quantity of each product. Modify the `inventory` dictionary accordingly.\n",
+    "\n",
+    "10. Print the updated inventory, displaying the quantity of each product on separate lines.\n",
+    "\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": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1\n",
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 2\n",
+    "inventory = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Please provide number or t-shirt available:  2\n",
+      "Please provide number or mug available:  3\n",
+      "Please provide number or hat available:  4\n",
+      "Please provide number or book available:  5\n",
+      "Please provide number or keychain available:  6\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 3\n",
+    "for product in products:\n",
+    "    inventory[product] = input(f\"Please provide number of {product} available: \")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 4\n",
+    "customer_orders = set()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Please add product number 1 to the order:  book\n",
+      "Please add product number 2 to the order:  hat\n",
+      "Please add product number 3 to the order:  keychain\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 5\n",
+    "for i in range(3):\n",
+    "    customer_orders.add(input(f\"Please add product number {i + 1} to the order: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The products in the order are: {'keychain', 'book', 'hat'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 6\n",
+    "print(f\"The products in the order are: {customer_orders}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The number of products in the order is 3.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 7\n",
+    "order_length = len(customer_orders)\n",
+    "print(f\"The number of products in the order is {order_length}.\")\n",
+    "\n",
+    "products_length = len(products)\n",
+    "\n",
+    "total_products = 0\n",
+    "for product in products:\n",
+    "    total_products += int(inventory[product])\n",
+    "\n",
+    "perc_ordered = (order_length / total_products) * 100\n",
+    "\n",
+    "stats_tuple = (products_length, perc_ordered)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Products Ordered: 17.647058823529413%\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 8\n",
+    "print(\"Order Statistics:\")\n",
+    "print(f\"Total Products Ordered: {order_length}\")\n",
+    "print(f\"Percentage of Products Ordered: {perc_ordered}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 9\n",
+    "for product in customer_orders:\n",
+    "    if product in inventory.keys():\n",
+    "        prod = int(inventory[product])\n",
+    "        prod -= 1\n",
+    "        inventory[product] = str(prod)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t-shirt: 2\n",
+      "mug: 3\n",
+      "hat: 3\n",
+      "book: 4\n",
+      "keychain: 5\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 10\n",
+    "for product in products:\n",
+    "    print(f\"{product}: {inventory[product]}\")"
+   ]
+  }
+ ],
+ "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": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/lab-python-data-structures.ipynb b/lab-python-data-structures.ipynb
index 5b3ce9e0..de644361 100644
--- a/lab-python-data-structures.ipynb
+++ b/lab-python-data-structures.ipynb
@@ -50,13 +50,204 @@
     "\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": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1\n",
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 2\n",
+    "inventory = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Please provide number or t-shirt available:  2\n",
+      "Please provide number or mug available:  3\n",
+      "Please provide number or hat available:  4\n",
+      "Please provide number or book available:  5\n",
+      "Please provide number or keychain available:  6\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 3\n",
+    "for product in products:\n",
+    "    inventory[product] = input(f\"Please provide number of {product} available: \")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 4\n",
+    "customer_orders = set()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Please add product number 1 to the order:  book\n",
+      "Please add product number 2 to the order:  hat\n",
+      "Please add product number 3 to the order:  keychain\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 5\n",
+    "for i in range(3):\n",
+    "    customer_orders.add(input(f\"Please add product number {i + 1} to the order: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The products in the order are: {'keychain', 'book', 'hat'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 6\n",
+    "print(f\"The products in the order are: {customer_orders}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The number of products in the order is 3.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 7\n",
+    "order_length = len(customer_orders)\n",
+    "print(f\"The number of products in the order is {order_length}.\")\n",
+    "\n",
+    "products_length = len(products)\n",
+    "\n",
+    "total_products = 0\n",
+    "for product in products:\n",
+    "    total_products += int(inventory[product])\n",
+    "\n",
+    "perc_ordered = (order_length / total_products) * 100\n",
+    "\n",
+    "stats_tuple = (products_length, perc_ordered)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Order Statistics:\n"
+     ]
+    },
+    {
+     "ename": "NameError",
+     "evalue": "name 'order_length' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[2], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# 8\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOrder Statistics:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTotal Products Ordered: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00morder_length\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPercentage of Products Ordered: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mperc_ordered\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'order_length' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "# 8\n",
+    "print(\"Order Statistics:\")\n",
+    "print(f\"Total Products Ordered: {order_length}\")\n",
+    "print(f\"Percentage of Products Ordered: {perc_ordered}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 9\n",
+    "for product in customer_orders:\n",
+    "    if product in inventory.keys():\n",
+    "        prod = int(inventory[product])\n",
+    "        prod -= 1\n",
+    "        inventory[product] = str(prod)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t-shirt: 2\n",
+      "mug: 3\n",
+      "hat: 3\n",
+      "book: 4\n",
+      "keychain: 5\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 10\n",
+    "for product in products:\n",
+    "    print(f\"{product}: {inventory[product]}\")"
+   ]
   }
  ],
  "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 +259,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,