Solved Lab- Data Structures

lab-python-data-structures.ipynb

@@ -50,11 +50,97 @@
     "\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": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'t-shirt': 5, 'mug': 5, 'hat': 5, 'book': 5, 'keychain': 5}\n",
+      "New orders are as follows: {'hat', 'book', 'mug'}\n",
+      "Order Statistics:\n",
+      "Total Products Ordered: 3\n",
+      "Percentage of Products Ordered: 60.0 %\n",
+      "Updated Inventory:\n",
+      "Amount of t-shirts in the inventory: 5\n",
+      "Amount of mugs in the inventory: 4\n",
+      "Amount of hats in the inventory: 4\n",
+      "Amount of books in the inventory: 4\n",
+      "Amount of keychains in the inventory: 5\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Define a list\n",
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "# Create empty dictionary\n",
+    "inventory = {}\n",
+    "# Ask for input for each product\n",
+    "inventory[\"t-shirt\"] = int(input(\"Enter the quantity of the t-shirt: \"))\n",
+    "inventory[\"mug\"] = int(input(\"Enter the quantity of the mug: \"))\n",
+    "inventory[\"hat\"] = int(input(\"Enter the quantity of the hat: \"))\n",
+    "inventory[\"book\"] = int(input(\"Enter the quantity of the book: \"))\n",
+    "inventory[\"keychain\"] = int(input(\"Enter the quantity of the keychain: \"))\n",
+    "\n",
+    "print(inventory)\n",
+    "# Empty set \n",
+    "customer_orders = set()\n",
+    "\n",
+    "# Three products orders from the customer\n",
+    "order_1 = input(\"Enter product 1: \").strip().lower()\n",
+    "order_2 = input(\"Enter product 2: \").strip().lower()\n",
+    "order_3 = input(\"Enter product 3: \").strip().lower()\n",
+    "\n",
+    "# validation\n",
+    "if order_1 in products: \n",
+    "    customer_orders.add(order_1)\n",
+    "if order_2 in products:\n",
+    "    customer_orders.add(order_2)\n",
+    "if order_3 in products:\n",
+    "    customer_orders.add(order_3)\n",
+    "\n",
+    "# Print orders\n",
+    "print(f\"New orders are as follows: {customer_orders}\")\n",
+    "\n",
+    "# Calculate order statistics\n",
+    "total_products_ordered = len(customer_orders)\n",
+    "percentage_ordered = (total_products_ordered / len(products)) * 100\n",
+    "order_status= (total_products_ordered, percentage_ordered)\n",
+    "\n",
+    "# Print statistics\n",
+    "print(\"Order Statistics:\")\n",
+    "print(f\"Total Products Ordered: {order_status[0]}\")\n",
+    "print(f\"Percentage of Products Ordered: {order_status[1]} %\")\n",
+    "\n",
+    "#Update inventory\n",
+    "if \"t-shirt\" in customer_orders and inventory[\"t-shirt\"] > 0:\n",
+    "    inventory[\"t-shirt\"] -= 1\n",
+    "if \"mug\" in customer_orders and inventory[\"mug\"] > 0:\n",
+    "    inventory[\"mug\"] -= 1\n",
+    "if \"hat\" in customer_orders and inventory[\"hat\"] > 0:\n",
+    "    inventory[\"hat\"] -= 1\n",
+    "if \"book\" in customer_orders and inventory[\"book\"] > 0:\n",
+    "    inventory[\"book\"] -= 1\n",
+    "if \"keychain\" in customer_orders and inventory[\"keychain\"] > 0:\n",
+    "    inventory[\"keychain\"] -= 1\n",
+    "\n",
+    "# Print inventory\n",
+    "print(\"Updated Inventory:\")\n",
+    "print(f\"Amount of t-shirts in the inventory: {inventory['t-shirt']}\")\n",
+    "print(f\"Amount of mugs in the inventory: {inventory['mug']}\")\n",
+    "print(f\"Amount of hats in the inventory: {inventory['hat']}\")\n",
+    "print(f\"Amount of books in the inventory: {inventory['book']}\")\n",
+    "print(f\"Amount of keychains in the inventory: {inventory['keychain']}\")"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "base",
    "language": "python",
    "name": "python3"
   },
@@ -68,7 +154,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,