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Complete data structures lab #600

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Complete data structures lab
avisivid-hrda Oct 17, 2025
d34bdf7
Add an empty set
avisivid-hrda Oct 17, 2025
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146 changes: 143 additions & 3 deletions lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,10 @@
]
},
{
"cell_type": "markdown",
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"## Exercise: Managing Customer Orders\n",
"\n",
Expand All @@ -21,8 +23,10 @@
"\n",
"1. Define a list called `products` that contains the following items: \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\".\n",
"\n",
"\n",
"2. Create an empty dictionary called `inventory`.\n",
"\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.\n",
"\n",
"4. Create an empty set called `customer_orders`.\n",
Expand Down Expand Up @@ -50,11 +54,147 @@
"\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": 6,
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"inventory = {}\n",
"\n",
"for product in products:\n",
" quantity = int(input(f\"Enter the number of {product} available in the inventory\"))\n",
" inventory[product] = quantity #name_of_the_dictionary(key) = output variable (or) value for the key\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 76, 'mug': 22, 'hat': 81, 'book': 60, 'keychain': 3}\n"
]
}
],
"source": [
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"customer_orders = set()\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"order = input(f\"Please enter the name of any three products from {products} you want to order:\")\n",
"final_order = [item.strip() for item in order.split(\",\")] \n",
"#without stripping and splitting, the items either appear duplicated or with spaces\n",
"#so strip function is carried out for each item that is split\n",
"customer_orders = set(final_order)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'mug', 't-shirt', 'book'}\n"
]
}
],
"source": [
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"total_products_ordered = len(customer_orders)\n",
"percentage_of_the_products_ordered = (total_products_ordered / (len(products)))*100\n",
"order_status = (total_products_ordered, percentage_of_the_products_ordered) "
]
},
{
"cell_type": "code",
"execution_count": 11,
"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(\"Order Statistics:\")\n",
"print(f\"Total Products Ordered:\", int(total_products_ordered))\n",
"print(f\"Percentage of Products Ordered:\", str(percentage_of_the_products_ordered) + '%')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"inventory = {'t-shirt': 76, 'mug': 22, 'hat': 81, 'book': 60, 'keychain': 3}\n",
"\n",
"for product, quantity in inventory.items():\n",
" inventory[product] = quantity -1 #dictionary_name[key] = value -1 (this will assign the value to the respective keys)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"t-shirt: 75\n",
"mug: 21\n",
"hat: 80\n",
"book: 59\n",
"keychain: 2\n"
]
}
],
"source": [
"for product, quantity in inventory.items():\n",
" print(f\"{product}: {quantity}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -68,7 +208,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.7"
}
},
"nbformat": 4,
Expand Down