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222 changes: 219 additions & 3 deletions lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -50,13 +50,229 @@
"\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": 1,
"metadata": {},
"outputs": [],
"source": [
"#1 Define a list called products that contains the following items: \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\".\n",
"products = [\"tshirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#2 Create an empty dictionary called inventory.\n",
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"enter the quantiy of t-shirts you want : 2\n",
"enter the quantiy of mugs you want : 3\n",
"enter the quantiy of hats you want : 4\n",
"enter the quantiy of books you want : 5\n",
"enter the quantiy of keychains you want : 6\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'tshirt': 2, 'mug': 3, 'hat': 4, 'book': 5, 'keychain': 6}\n"
]
}
],
"source": [
"#3 Ask the user to input the quantity of each product available in the inventory. \n",
"# Use the product names from the products list as keys in the inventory dictionary and assign the respective quantities as values.\n",
" \n",
"inventory[\"tshirt\"] = int(input(\"enter the quantiy of t-shirts you want : \"))\n",
"inventory[\"mug\"] = int(input(\"enter the quantiy of mugs you want : \"))\n",
"inventory[\"hat\"] = int(input(\"enter the quantiy of hats you want : \")) \n",
"inventory[\"book\"] = int(input(\"enter the quantiy of books you want : \")) \n",
"inventory[\"keychain\"] = int(input(\"enter the quantiy of keychains you want : \"))\n",
"\n",
"inventory.items()\n",
"print (inventory)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"#4 Create an empty set called customer_orders.\n",
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"enter a product your want to order: mug\n",
"enter a product your want to order: book\n",
"enter a product your want to order: hat\n"
]
}
],
"source": [
"#5 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\" or \"keychain\". \n",
"# Add each product name to the customer_orders set.\n",
"\n",
"for i in range (3): \n",
" x = input(\"enter a product your want to order: \")\n",
" while x not in products:\n",
" print(\"we don't have that product\")\n",
" x = input(\"enter a product your want to order: \")\n",
" customer_orders.add(x)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'book', 'mug', 'hat'}\n"
]
}
],
"source": [
"#6 Print the products in the customer_orders set.\n",
"print (customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3\n",
"60.0%\n",
"(3, 60.0)\n"
]
}
],
"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",
"#Store these statistics in a tuple called order_status\n",
"Total_Products_Ordered = len(customer_orders)\n",
"print (Total_Products_Ordered )\n",
"\n",
"Percentage_of_Products_Ordered = len(customer_orders) / len(products) * 100\n",
"print (f\"{Percentage_of_Products_Ordered}%\")\n",
"\n",
"order_status = (Total_Products_Ordered, Percentage_of_Products_Ordered)\n",
"print (order_status)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 60.0%\n"
]
}
],
"source": [
"#8 Print the order statistics using the following format:\n",
"#Order Statistics:\n",
"#Total Products Ordered: <total_products_ordered>\n",
"#Percentage of Products Ordered: <percentage_ordered>% \n",
"print(f\"Total Products Ordered: {Total_Products_Ordered}\")\n",
"print(f\"Percentage of Products Ordered: {Percentage_of_Products_Ordered}%\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'tshirt': 1, 'mug': 2, 'hat': 3, 'book': 4, 'keychain': 5}\n"
]
}
],
"source": [
"#9 Update the inventory by subtracting 1 from the quantity of each product. Modify the inventory dictionary accordingly.\n",
"\n",
"for key in inventory :\n",
" new_quantity = inventory[key] - 1\n",
" inventory[key] = new_quantity\n",
"\n",
"print (inventory)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'tshirt': 1, 'mug': 2, 'hat': 3, 'book': 4, 'keychain': 5}\n"
]
}
],
"source": [
"#10 Print the updated inventory, displaying the quantity of each product on separate lines.\n",
"print(inventory) "
]
},
{
"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": {
Expand All @@ -68,7 +284,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
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