Skip to content

Update lab-python-data-structures.ipynb #764

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
Orgo4ever wants to merge 2 commits into
base: main
Choose a base branch
from
Open

Update lab-python-data-structures.ipynb #764

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
6839f5f
Update lab-python-data-structures.ipynb
Orgo4ever Jun 16, 2026
ac00b5c
Update lab-python-data-structures.ipynb
Orgo4ever Jul 5, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
235 changes: 233 additions & 2 deletions lab-python-data-structures.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -50,11 +50,242 @@
"\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": 61,
"metadata": {},
"outputs": [],
"source": [
"# This is Kyle Solving the Lab"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"products= [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"inventory={}"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
"t_shirt_quantity=int(input(\"Enter the quantity of t-shirsts:\"))\n",
"mug_quantity=int(input(\"Enter the quantity of mugs:\"))\n",
"hat_quantity=int(input(\"Enter the quantity of hats:\"))\n",
"book_quantity=int(input(\"Enter the quantity of mugs:\"))\n",
"keychain_quantity=int(input(\"Enter the quantity of keychains:\"))"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [],
"source": [
"inventory={\"t-shirt\": t_shirt_quantity, \n",
"\"mug\": mug_quantity, \n",
"\"hat\": hat_quantity, \n",
"\"book\": book_quantity, \n",
"\"keychain\": keychain_quantity }"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 5, 'mug': 5, 'hat': 5, 'book': 5, 'keychain': 5}"
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inventory"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [],
"source": [
"customer_orders={}"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [],
"source": [
"order_1=input(\"Please enter a product to order:\")\n",
"order_2= input(\"Please enter a product to order:\")\n",
"order_3=input(\"Please enter a product to order:\")\n",
"order_= input(\"Please enter a product to order:\")\n"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'mug', 'keychain', 'hat'}\n"
]
}
],
"source": [
"customer_orders={order_1, order_2, order_3}\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(3, 60.0)\n"
]
}
],
"source": [
"products_ordered= len(customer_orders)\n",
"percentage_ordered= len(customer_orders)/len(products)*100\n",
"order_statistics=(products_ordered, percentage_ordered,)\n",
"print(order_statistics)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 3, 'mug': 3, 'hat': 3, 'book': 3, 'keychain': 3}\n"
]
}
],
"source": [
"inventory[\"t-shirt\"]=inventory[\"t-shirt\"]-1\n",
"inventory[\"mug\"]=inventory[\"mug\"]-1\n",
"inventory[\"book\"]=inventory[\"book\"]-1\n",
"inventory[\"hat\"]=inventory[\"hat\"]-1\n",
"inventory[\"keychain\"]=inventory[\"keychain\"]-1\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"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 +299,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.9.10"
}
},
"nbformat": 4,
Expand Down