diff --git a/.gitignore b/.gitignore new file mode 100644 index 00000000..763513e9 --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +.ipynb_checkpoints diff --git a/lab-python-data-structures.ipynb b/lab-python-data-structures.ipynb index 5b3ce9e0..1f76c4c0 100644 --- a/lab-python-data-structures.ipynb +++ b/lab-python-data-structures.ipynb @@ -50,6 +50,313 @@ "\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": [ + "\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." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "inventory = {}" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Enter the number of t-shirt: 2\n", + "Enter the number of mug: 3\n", + "Enter the number of hat: 4\n", + "Enter the number of book: 56\n", + "Enter the number of keychain: 8\n" + ] + } + ], + "source": [ + "for item in products:\n", + " quantity = int(input(f\"Enter the number of {item}: \"))\n", + " inventory[item] = quantity" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'t-shirt': 2, 'mug': 3, 'hat': 4, 'book': 56, 'keychain': 8}" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inventory" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "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." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "customer_orders = set()" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Name 1 product: from ['t-shirt', 'mug', 'hat', 'book', 'keychain'] list: book\n", + "Name 1 product: from ['t-shirt', 'mug', 'hat', 'book', 'keychain'] list: keychain\n", + "Name 1 product: from ['t-shirt', 'mug', 'hat', 'book', 'keychain'] list: mug\n" + ] + } + ], + "source": [ + "for item in range(3):\n", + " order = input(f\"Name 1 product: from {products} list: \")\n", + " customer_orders.add(order)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'book', 'keychain', 'mug'}" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "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.\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: \n", + " Percentage of Products Ordered: % \n", + " ```" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [], + "source": [ + "total_orders = len(customer_orders)\n", + "\n", + "percentage = (total_orders / len(products) * 100)\n", + "\n", + "order_status = (total_orders, percentage)" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3, 60.0)" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "order_status" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Order Statistics:\n", + "Total Products Ordered: 3\n", + "Percentage of Products Ordered: 60.0%\n" + ] + } + ], + "source": [ + "print(f\"\"\"Order Statistics:\n", + "Total Products Ordered: {order_status[0]}\n", + "Percentage of Products Ordered: {order_status[1]}%\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "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." + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'t-shirt': 2, 'mug': 2, 'hat': 4, 'book': 55, 'keychain': 7}" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inventory" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'book', 'keychain', 'mug'}" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer_orders" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [], + "source": [ + "for item in customer_orders:\n", + " inventory[item] -= 1" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'t-shirt': 2, 'mug': 1, 'hat': 4, 'book': 54, 'keychain': 6}" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inventory" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "t-shirt: 2\n", + "mug: 1\n", + "hat: 4\n", + "book: 54\n", + "keychain: 6\n" + ] + } + ], + "source": [ + "for keys, values in inventory.items():\n", + " print(f\"{keys}: {values}\")" + ] } ], "metadata": { @@ -68,7 +375,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.14.7" } }, "nbformat": 4,