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lab done #530

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233 changes: 230 additions & 3 deletions lab-python-data-structures.ipynb
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Expand Up @@ -50,13 +50,240 @@
"\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": 33,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please enter the quantity of t-shirt 5\n",
"Please enter the quantity of mug 6\n",
"Please enter the quantity of hat 7\n",
"Please enter the quantity of book 8\n",
"Please enter the quantity of keychain 9\n"
]
}
],
"source": [
"#1.Define a list \n",
"product_1 = \"t-shirt\"\n",
"product_2 = \"mug\"\n",
"product_3 = \"hat\"\n",
"product_4 = \"book\"\n",
"product_5 = \"keychain\"\n",
"\n",
"products = [product_1, product_2, product_3, product_4, product_5]\n",
"products\n",
"\n",
"#2.Create an empty dictionary called inventory\n",
"inventory = {}\n",
"\n",
"#3.1.Ask the user to input the quantity of each product available in the inventory.\n",
"question_1 = int(input(f\"Please enter the quantity of {product_1}\"))\n",
"question_2 = int(input(f\"Please enter the quantity of {product_2}\"))\n",
"question_3 = int(input(f\"Please enter the quantity of {product_3}\"))\n",
"question_4 = int(input(f\"Please enter the quantity of {product_4}\"))\n",
"question_5 = int(input(f\"Please enter the quantity of {product_5}\"))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 5, 'mug': 6, 'hat': 7, 'book': 8, 'keychain': 9}\n"
]
}
],
"source": [
"#3.2.Use the product names from the products list as keys in the inventory dictionary \n",
"#and assign the respective quantities as values.\n",
"\n",
"inventory = {\n",
" product_1: question_1,\n",
" product_2: question_2,\n",
" product_3: question_3,\n",
" product_4: question_4,\n",
" product_5: question_5,\n",
"}\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"#4.Create an empty set called customer_orders\n",
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter the name of the first product: mug\n",
"Enter the name of the second product: book\n",
"Enter the name of the third product: hat\n"
]
}
],
"source": [
"#5.1.Ask the user to input the name of three products that a customer wants to order \n",
"#(from those in the products list, meaning three products out of \"t-shirt\", \"mug\", \"hat\", \"book\" \n",
"#or \"keychain\". \n",
"\n",
"order1 = input(\"Enter the name of the first product: \").strip().lower()\n",
"order2 = input(\"Enter the name of the second product: \").strip().lower()\n",
"order3 = input(\"Enter the name of the third product: \").strip().lower()\n",
"\n",
"# Add only valid products to the set\n",
"for order in [order1, order2, order3]:\n",
" if order in products:\n",
" customer_orders.add(order)\n",
" else:\n",
" print(f\"'{order}' is not a valid product.\")\n",
"\n",
"#Add each product name to the customer_orders set.\n",
"customer_orders = set()\n",
"customer_orders.add(order1)\n",
"customer_orders.add(order2)\n",
"customer_orders.add(order3)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Customer orders: {'hat', 'mug', 'book'}\n"
]
}
],
"source": [
"#5.2.Add each product name to the customer_orders set.\n",
"print(\"Customer orders:\", customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3\n"
]
}
],
"source": [
"#Total Products Ordered: The total number of products in the customer_orders set.\n",
"print(len(customer_orders))"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"#7.Percentage of Products Ordered: The percentage of products ordered compared to the total available products.\n",
"\n",
"total_products_ordered = len(customer_orders)\n",
"percentage_ordered = (total_products_ordered/len(products))*100\n",
"\n",
"order_stats = (total_products_ordered, percentage_ordered)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics: \n",
"Total Products Ordered: 3\n",
"Percentage of Unique products ordered: 60.0\n"
]
}
],
"source": [
"#8.Print the order statistics using the following format:\n",
"\n",
"print(\"Order Statistics: \")\n",
"print(\"Total Products Ordered: \", order_stats[0])\n",
"print(\"Percentage of Unique products ordered: \", order_stats[1])"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"#9.Update the inventory by subtracting 1 from the quantity of each product. Modify the inventory dictionary accordingly.\n",
"\n",
"product_1 = list(customer_orders)[0]\n",
"inventory[product_1] -=1\n",
"\n",
"product_2 = list(customer_orders)[1]\n",
"inventory[product_2] -=1\n",
"\n",
"product_3 = list(customer_orders)[2]\n",
"inventory[product_3] -=1\n"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 5, 'mug': 3, 'hat': 4, 'book': 5, 'keychain': 9}"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#10.Print the updated inventory, displaying the quantity of each product on separate lines.\n",
"\n",
"inventory"
]
}
],
"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": {
Expand All @@ -68,7 +295,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
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