From ef3714a66ae1f521271c4a90a3fe381166be8e14 Mon Sep 17 00:00:00 2001 From: Ha Nguyen Date: Thu, 15 Jan 2026 14:46:25 +0100 Subject: [PATCH] lab-python-data-structures.ipynb --- lab-python-data-structures.ipynb | 138 ++++++++++++++++++++++++++++++- 1 file changed, 136 insertions(+), 2 deletions(-) diff --git a/lab-python-data-structures.ipynb b/lab-python-data-structures.ipynb index 5b3ce9e0..c49c1d12 100644 --- a/lab-python-data-structures.ipynb +++ b/lab-python-data-structures.ipynb @@ -50,11 +50,145 @@ "\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": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'t-shirt': 10, 'mug': 10, 'hat': 10, 'book': 10, 'keychain': 10}\n" + ] + } + ], + "source": [ + "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n", + "inventory = {}\n", + "\n", + "for product in products:\n", + " quantity = int(input(f\"Enter quantity of {[product]}: \"))\n", + " inventory[product] = quantity\n", + "\n", + "print(inventory)\n", + "customer_orders = set()\n", + "product_orders = input(\"Enter 3 products you want to order (separated by commas): \")\n", + "for product_name in product_orders.split(\",\"):\n", + " product_name = product_name.strip()\n", + " customer_orders.add(product_name)\n", + "print(customer_orders)\n", + "total_product_ordered = len(customer_orders)\n", + "print(f\"You have ordered {total_product_ordered} products.\")\n", + "percentage_products_ordered = (total_product_ordered / len(products)) * 100\n", + "print(f\"You have ordered {percentage_products_ordered}% of all available products.\")\n", + "order_status = ((\"total_product_ordered\", total_product_ordered),(\"percentage_products_ordered\", percentage_products_ordered))\n", + "print(order_status)\n", + "print(\"Order stastistics\\n\") \n", + "print(order_status)\n", + "print(customer_orders)\n", + "for product in customer_orders:\n", + " inventory[product] -= 1\n", + "\n", + "print(inventory)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "base", "language": "python", "name": "python3" }, @@ -68,7 +202,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.13.5" } }, "nbformat": 4,