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..c78d8635
--- /dev/null
+++ b/.ipynb_checkpoints/lab-python-data-structures-checkpoint.ipynb
@@ -0,0 +1,423 @@
+{
+ "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": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1. Define a list called `products` that contains the following items: \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "products = [\"T-shirt\", \"Mug\", \"Hat\", \"Book\", \"Keychain\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2 Create an empty dictionary called `inventory`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inventory = {} "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Input T-shirts quantity:  4\n",
+      "Input Mug quantity:  3\n",
+      "Input Hat quantity:  2\n",
+      "Input Book quantity:  1\n",
+      "Input Keychain quantity:  5\n"
+     ]
+    }
+   ],
+   "source": [
+    "inventory[products[0]] = int(input(\"Input T-shirts quantity: \"))\n",
+    "inventory[products[1]] = int(input(\"Input Mug quantity: \"))\n",
+    "inventory[products[2]] = int(input(\"Input Hat quantity: \"))\n",
+    "inventory[products[3]] = int(input(\"Input Book quantity: \"))\n",
+    "inventory[products[4]] = int(input(\"Input Keychain quantity: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'T-shirt': 4, 'Mug': 3, 'Hat': 2, 'Book': 1, 'Keychain': 5}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(inventory)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4 Create an empty set called `customer_orders`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "customer_orders = set()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain mug\n",
+      "Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain hat\n",
+      "Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain book\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Successe\n"
+     ]
+    }
+   ],
+   "source": [
+    "Item1 = input(\"Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain\").title()\n",
+    "Item2 = input(\"Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain\").title()\n",
+    "Item3 = input(\"Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain\").title()\n",
+    "if Item1 in products and Item2 in products and Item3 in products:\n",
+    "    customer_orders.update([Item1,Item2,Item3])\n",
+    "    print(\"Successe\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# customer_orders.difference_update([\"Mug\", \"Hat\", \"Book\"]) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 6. Print the products in the `customer_orders` set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'Book', 'Mug', 'Hat'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(customer_orders)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3\n"
+     ]
+    }
+   ],
+   "source": [
+    "Total_Products_Ordered = len(customer_orders)\n",
+    "print(Total_Products_Ordered)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20%\n"
+     ]
+    }
+   ],
+   "source": [
+    "Percentage_of_Products_Ordered = Total_Products_Ordered / sum(inventory.values()) * 100\n",
+    "print(str(round(Percentage_of_Products_Ordered))  + \"%\"  )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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",
+    "   ```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Products Ordered: 20%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Order Statistics:\\nTotal Products Ordered: {Total_Products_Ordered}\\nPercentage of Products Ordered: {round(Percentage_of_Products_Ordered)}%\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 9. Update the inventory by subtracting 1 from the quantity of each product. Modify the `inventory` dictionary accordingly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for item in customer_orders & inventory.keys():\n",
+    "    # inventory[item] -= 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if Item1 in inventory and Item1 in customer_orders:\n",
+    "    inventory[Item1] -= 1\n",
+    "if Item2 in inventory and Item2 in customer_orders:\n",
+    "    inventory[Item2] -= 1\n",
+    "if Item3 in inventory and Item3 in customer_orders:\n",
+    "    inventory[Item3] -= 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 10. Print the updated inventory, displaying the quantity of each product on separate lines."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dict_items([('T-shirt', 4), ('Mug', 3), ('Hat', 2), ('Book', 1), ('Keychain', 5)])\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Before\n",
+    "print(inventory.items())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dict_items([('T-shirt', 4), ('Mug', 2), ('Hat', 1), ('Book', 0), ('Keychain', 5)])\n"
+     ]
+    }
+   ],
+   "source": [
+    "# After:\n",
+    "print(inventory.items())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "T-shirt: 4\n",
+      "Mug: 2\n",
+      "Hat: 1\n",
+      "Book: 0\n",
+      "Keychain: 5\n"
+     ]
+    }
+   ],
+   "source": [
+    "for product, qty in inventory.items():\n",
+    "    print(f\"{product}: {qty}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "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": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/lab-python-data-structures.ipynb b/lab-python-data-structures.ipynb
index 5b3ce9e0..c78d8635 100644
--- a/lab-python-data-structures.ipynb
+++ b/lab-python-data-structures.ipynb
@@ -50,13 +50,360 @@
     "\n",
     "Solve the exercise by implementing the steps using the Python concepts of lists, dictionaries, sets, and basic input/output operations. "
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1. Define a list called `products` that contains the following items: \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "products = [\"T-shirt\", \"Mug\", \"Hat\", \"Book\", \"Keychain\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2 Create an empty dictionary called `inventory`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inventory = {} "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Input T-shirts quantity:  4\n",
+      "Input Mug quantity:  3\n",
+      "Input Hat quantity:  2\n",
+      "Input Book quantity:  1\n",
+      "Input Keychain quantity:  5\n"
+     ]
+    }
+   ],
+   "source": [
+    "inventory[products[0]] = int(input(\"Input T-shirts quantity: \"))\n",
+    "inventory[products[1]] = int(input(\"Input Mug quantity: \"))\n",
+    "inventory[products[2]] = int(input(\"Input Hat quantity: \"))\n",
+    "inventory[products[3]] = int(input(\"Input Book quantity: \"))\n",
+    "inventory[products[4]] = int(input(\"Input Keychain quantity: \"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'T-shirt': 4, 'Mug': 3, 'Hat': 2, 'Book': 1, 'Keychain': 5}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(inventory)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4 Create an empty set called `customer_orders`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "customer_orders = set()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain mug\n",
+      "Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain hat\n",
+      "Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain book\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Successe\n"
+     ]
+    }
+   ],
+   "source": [
+    "Item1 = input(\"Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain\").title()\n",
+    "Item2 = input(\"Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain\").title()\n",
+    "Item3 = input(\"Please chose up to 3 of these products: t-shirt , mug, hat, book, keychain\").title()\n",
+    "if Item1 in products and Item2 in products and Item3 in products:\n",
+    "    customer_orders.update([Item1,Item2,Item3])\n",
+    "    print(\"Successe\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# customer_orders.difference_update([\"Mug\", \"Hat\", \"Book\"]) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 6. Print the products in the `customer_orders` set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'Book', 'Mug', 'Hat'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(customer_orders)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3\n"
+     ]
+    }
+   ],
+   "source": [
+    "Total_Products_Ordered = len(customer_orders)\n",
+    "print(Total_Products_Ordered)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20%\n"
+     ]
+    }
+   ],
+   "source": [
+    "Percentage_of_Products_Ordered = Total_Products_Ordered / sum(inventory.values()) * 100\n",
+    "print(str(round(Percentage_of_Products_Ordered))  + \"%\"  )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 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",
+    "   ```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Products Ordered: 20%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Order Statistics:\\nTotal Products Ordered: {Total_Products_Ordered}\\nPercentage of Products Ordered: {round(Percentage_of_Products_Ordered)}%\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 9. Update the inventory by subtracting 1 from the quantity of each product. Modify the `inventory` dictionary accordingly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for item in customer_orders & inventory.keys():\n",
+    "    # inventory[item] -= 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if Item1 in inventory and Item1 in customer_orders:\n",
+    "    inventory[Item1] -= 1\n",
+    "if Item2 in inventory and Item2 in customer_orders:\n",
+    "    inventory[Item2] -= 1\n",
+    "if Item3 in inventory and Item3 in customer_orders:\n",
+    "    inventory[Item3] -= 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 10. Print the updated inventory, displaying the quantity of each product on separate lines."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dict_items([('T-shirt', 4), ('Mug', 3), ('Hat', 2), ('Book', 1), ('Keychain', 5)])\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Before\n",
+    "print(inventory.items())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dict_items([('T-shirt', 4), ('Mug', 2), ('Hat', 1), ('Book', 0), ('Keychain', 5)])\n"
+     ]
+    }
+   ],
+   "source": [
+    "# After:\n",
+    "print(inventory.items())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "T-shirt: 4\n",
+      "Mug: 2\n",
+      "Hat: 1\n",
+      "Book: 0\n",
+      "Keychain: 5\n"
+     ]
+    }
+   ],
+   "source": [
+    "for product, qty in inventory.items():\n",
+    "    print(f\"{product}: {qty}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "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": {
@@ -68,7 +415,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,