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lab data structures solutions #595

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4 changes: 4 additions & 0 deletions .vscode/settings.json
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Original file line number Diff line number Diff line change
@@ -0,0 +1,4 @@
{
"python-envs.defaultEnvManager": "ms-python.python:system",
"python-envs.pythonProjects": []
}
209 changes: 207 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 +50,216 @@
"\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": 25,
"metadata": {},
"outputs": [],
"source": [
"# 1.Define a LIST called `products` that contains the following items:\n",
"# \"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\".\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"# 2. Create an empty DICTIONARY called `inventory`\n",
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Inventory: {'t-shirt': 4, 'mug': 5, 'hat': 6, 'book': 7, 'keychain': 8}\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\n",
"# and assign the respective quantities as values.\n",
"\n",
"inventory[products[0]] = int(input(f\"Enter quantity for {products[0]}: \"))\n",
"inventory[products[1]] = int(input(f\"Enter quantity for {products[1]}: \"))\n",
"inventory[products[2]] = int(input(f\"Enter quantity for {products[2]}: \"))\n",
"inventory[products[3]] = int(input(f\"Enter quantity for {products[3]}: \"))\n",
"inventory[products[4]] = int(input(f\"Enter quantity for {products[4]}: \"))\n",
"\n",
"\n",
"\n",
"# Print the `inventory` dictionary to see the available products and their quantities.\n",
"print(\"Inventory: \", inventory)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"#4. Create an empty SET called `customer_orders`\n",
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"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, \n",
"# meaning three products out of \"t-shirt\", \"mug\", \"hat\", \"book\" or \"keychain\".\n",
"# Add each product name to the `customer_orders` set.\n",
"customer_orders.add(input(\"Enter the first product to order from those in the products list: \"))\n",
"customer_orders.add(input(\"Enter the second product to order from those in the products list: \"))\n",
"customer_orders.add(input(\"Enter the third product to order from those in the products list: \"))\n"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Products in the customer orders: {'keychain', 'book', 't-shirt'}\n"
]
}
],
"source": [
"#6. Print the products in the `customer_orders` set.\n",
"print (\"Products in the customer orders: \", customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total Products Ordered: {3}\n",
"Percentage of Products Ordered: {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",
"tot_products_ordered = len(customer_orders)\n",
"print(f\"Total Products Ordered:\", {tot_products_ordered})\n",
" \n",
"# - Percentage of Products Ordered:\n",
"# The percentage of products ordered compared to the total available products.\n",
"percentage_products_ordered = tot_products_ordered / len(products) * 100\n",
"print(\"Percentage of Products Ordered:\", {percentage_products_ordered}, \"%\")\n",
"\n",
"# Store these statistics in a tuple called `order_status`\n",
"order_status = (tot_products_ordered, percentage_products_ordered)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 60.0% \n",
" \n"
]
}
],
"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",
"# ```\n",
"print(f\"\"\"Order Statistics:\n",
"Total Products Ordered: {tot_products_ordered}\n",
"Percentage of Products Ordered: {percentage_products_ordered}% \n",
" \"\"\")"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"# 9. Update the inventory by subtracting 1 from the quantity of each product.\n",
"# Modify the `inventory` dictionary accordingly.\n",
"inventory[products[0]] = inventory[products[0]] - 1\n",
"inventory[products[1]] = inventory[products[1]] - 1\n",
"inventory[products[2]] = inventory[products[2]] - 1\n",
"inventory[products[3]] = inventory[products[3]] - 1\n",
"inventory[products[4]] = inventory[products[4]] - 1\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Updated inventory:\n",
"t-shirt: 3 \n",
"mug: 4 \n",
"hat: 5 \n",
"book: 6 \n",
"keychain: 7 \n",
"\n"
]
}
],
"source": [
"# 10. Print the updated inventory, displaying the quantity of each product on separate lines.\n",
"print(f\"\"\" Updated inventory:\n",
"{products[0]}: {inventory[products[0]]} \n",
"{products[1]}: {inventory[products[1]]} \n",
"{products[2]}: {inventory[products[2]]} \n",
"{products[3]}: {inventory[products[3]]} \n",
"{products[4]}: {inventory[products[4]]} \n",
"\"\"\")\n"
]
},
{
"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 +273,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.12.9"
}
},
"nbformat": 4,
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