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lab-python-data-structures.ipynb #579

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Update lab-python-data-structures.ipynb
javiersoto16 Oct 6, 2025
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Update lab-python-data-structures.ipynb
javiersoto16 Oct 6, 2025
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263 changes: 261 additions & 2 deletions lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -50,11 +50,270 @@
"\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": [
"1. Define a list called `products` that contains the following items: \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['t-shirt', 'mug', 'hat', 'book', 'keychain']\n"
]
}
],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"print(products)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"2. Create an empty dictionary called `inventory`."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"inventory = {}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"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": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Inventory:\n",
"{'t-shirt': 5, 'mug': 10, 'hat': 7, 'book': 4, 'keychain': 2}\n"
]
}
],
"source": [
"valor_tshirt = int(input(f\"Enter the quantity of t-shirts avaliable: \"))\n",
"valor_mug = int(input(f\"Enter the quantity of mug avaliable: \"))\n",
"valor_hat = int(input(f\"Enter the quantity of hat avaliable: \"))\n",
"valor_book = int(input(f\"Enter the quantity of book avaliable: \"))\n",
"valor_keychain = int(input(f\"Enter the quantity of keychain avaliable: \"))\n",
"\n",
"\n",
"inventory = {\n",
" \"t-shirt\" : valor_tshirt,\n",
" \"mug\" : valor_mug,\n",
" \"hat\" : valor_hat,\n",
" \"book\" : valor_book,\n",
" \"keychain\" : valor_keychain\n",
"}\n",
"\n",
"print (\"Inventory:\")\n",
"print (inventory)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"4. Create an empty set called `customer_orders`."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"customer_orders = {}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"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."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"customer_orders = set()\n",
"\n",
"product1 = input(\"Ingresa el nombre del primer producto que deseas: \").lower()\n",
"product2 = input(\"Ingresa el nombre del segundo producto que deseas: \").lower()\n",
"product3 = input(\"Ingresa el nombre del tercer producto que deseas: \").lower()\n",
"\n",
"customer_orders.add(product1)\n",
"customer_orders.add(product2)\n",
"customer_orders.add(product3)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"6. Print the products in the `customer_orders` set."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'pencil', 'paper', 'pen'}\n"
]
}
],
"source": [
"print(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`."
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"total_products_ordered = len (customer_orders)\n",
"percentage_ordered = (total_products_ordered/len(products))*100\n",
"order_status =(total_products_ordered,percentage_ordered)\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"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": 35,
"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: {total_products_ordered}\")\n",
"print(f\"Percentage of products ordered: {percentage_ordered:}%\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"9. Update the inventory by subtracting 1 from the quantity of each product. Modify the `inventory` dictionary accordingly."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"inventory={}\n",
"\n",
"inventory[\"t-shirt\"] = valor_tshirt - 1\n",
"inventory[\"mug\"] = valor_mug - 1\n",
"inventory[\"hat\"] = valor_hat - 1\n",
"inventory[\"book\"] = valor_book - 1\n",
"inventory[\"keychain\"] = valor_keychain - 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"10. Print the updated inventory, displaying the quantity of each product on separate lines."
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Updated Inventory:\n",
"t-shirt: 4\n",
"mug: 9\n",
"hat: 6\n",
"book: 3\n",
"keychain: 1\n"
]
}
],
"source": [
"print(\"Updated Inventory:\")\n",
"print(f\"t-shirt: {inventory['t-shirt']}\")\n",
"print(f\"mug: {inventory['mug']}\")\n",
"print(f\"hat: {inventory['hat']}\")\n",
"print(f\"book: {inventory['book']}\")\n",
"print(f\"keychain: {inventory['keychain']}\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "base",
"language": "python",
"name": "python3"
},
Expand All @@ -68,7 +327,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
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