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Solved lab
maknaesuho Sep 14, 2026
78f9ca3
Ignore jupyter checkpoint folder
maknaesuho Sep 14, 2026
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1 change: 1 addition & 0 deletions .gitignore
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.ipynb_checkpoints
309 changes: 308 additions & 1 deletion lab-python-data-structures.ipynb
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Expand Up @@ -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: <total_products_ordered>\n",
" Percentage of Products Ordered: <percentage_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": {
Expand All @@ -68,7 +375,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.14.7"
}
},
"nbformat": 4,
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