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214 changes: 214 additions & 0 deletions .ipynb_checkpoints/lab-python-data-structures-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"# Lab | Data Structures "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"## Exercise: Managing Customer Orders\n",
"\n",
"As part of a business venture, you are starting an online store that sells various products. To ensure smooth operations, you need to develop a program that manages customer orders and inventory.\n",
"\n",
"Follow the steps below to complete the exercise:\n",
"\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.\n",
"\n",
"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.\n",
"\n",
"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",
" ```\n",
"\n",
"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.\n",
"\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": 68,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please enter the quantity of t-shirt (in kg): 10\n",
"Please enter the quantity of mug (in kg): 5\n",
"Please enter the quantity of hat (in kg): 12\n",
"Please enter the quantity of book (in kg): 14\n",
"Please enter the quantity of keychain (in kg): 1\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 10, 'mug': 5, 'hat': 12, 'book': 14, 'keychain': 1}\n"
]
}
],
"source": [
"# Define a list called products\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"# Create an empty dictionary\n",
"inventory = {}\n",
"# Quantity of each product\n",
"for product in products:\n",
" quantity = int(input(\"Please enter the quantity of \" + product + \" (in kg): \"))\n",
" inventory[product] = quantity\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please enter 1 product among: ['t-shirt', 'mug', 'hat', 'book', 'keychain'] mug\n",
"Please enter 1 product among: ['t-shirt', 'mug', 'hat', 'book', 'keychain'] book\n",
"Please enter 1 product among: ['t-shirt', 'mug', 'hat', 'book', 'keychain'] hat\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'hat', 'mug', 'book'}\n"
]
}
],
"source": [
"# Create an empty set\n",
"customer_orders = set()\n",
"# Set customer_orders top 3 products\n",
"while len(customer_orders) != 3:\n",
" customer_product = input(\"Please enter 1 product among: \" + str(products))\n",
" if customer_product in products:\n",
" customer_orders.add(customer_product)\n",
" else:\n",
" customer_product = input(\"Please enter 1 product among: \" + str(products))\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics: \n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered:60.0% \n"
]
}
],
"source": [
"Total_Products_Ordered = len(customer_orders)\n",
"Percentage_of_Products_Ordered = len(customer_orders) / len(products) *100\n",
"print(f\"Order Statistics: \")\n",
"print(f\"Total Products Ordered: {Total_Products_Ordered}\")\n",
"print(f\"Percentage of Products Ordered:{Percentage_of_Products_Ordered}% \")"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 9, 'mug': 4, 'hat': 11, 'book': 13, 'keychain': 0}\n"
]
}
],
"source": [
"# Update the inventory quantity\n",
"for key in inventory:\n",
" inventory[key]-= 1 # helped by the AI companion here because i don't understand why the code directly deduce 1 to the quantity without precising to work on the value itself\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"For t-shirt product, the updated quantity is:9 kg.\n",
"For mug product, the updated quantity is:4 kg.\n",
"For hat product, the updated quantity is:11 kg.\n",
"For book product, the updated quantity is:13 kg.\n",
"For keychain product, the updated quantity is:0 kg.\n"
]
}
],
"source": [
"for key, value in inventory.items():\n",
" print(f\"For {key} product, the updated quantity is:{value} kg.\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.9"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
142 changes: 140 additions & 2 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 Down Expand Up @@ -50,6 +52,142 @@
"\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": 68,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please enter the quantity of t-shirt (in kg): 10\n",
"Please enter the quantity of mug (in kg): 5\n",
"Please enter the quantity of hat (in kg): 12\n",
"Please enter the quantity of book (in kg): 14\n",
"Please enter the quantity of keychain (in kg): 1\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 10, 'mug': 5, 'hat': 12, 'book': 14, 'keychain': 1}\n"
]
}
],
"source": [
"# Define a list called products\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"# Create an empty dictionary\n",
"inventory = {}\n",
"# Quantity of each product\n",
"for product in products:\n",
" quantity = int(input(\"Please enter the quantity of \" + product + \" (in kg): \"))\n",
" inventory[product] = quantity\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please enter 1 product among: ['t-shirt', 'mug', 'hat', 'book', 'keychain'] mug\n",
"Please enter 1 product among: ['t-shirt', 'mug', 'hat', 'book', 'keychain'] book\n",
"Please enter 1 product among: ['t-shirt', 'mug', 'hat', 'book', 'keychain'] hat\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'hat', 'mug', 'book'}\n"
]
}
],
"source": [
"# Create an empty set\n",
"customer_orders = set()\n",
"# Set customer_orders top 3 products\n",
"while len(customer_orders) != 3:\n",
" customer_product = input(\"Please enter 1 product among: \" + str(products))\n",
" if customer_product in products:\n",
" customer_orders.add(customer_product)\n",
" else:\n",
" customer_product = input(\"Please enter 1 product among: \" + str(products))\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics: \n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered:60.0% \n"
]
}
],
"source": [
"Total_Products_Ordered = len(customer_orders)\n",
"Percentage_of_Products_Ordered = len(customer_orders) / len(products) *100\n",
"print(f\"Order Statistics: \")\n",
"print(f\"Total Products Ordered: {Total_Products_Ordered}\")\n",
"print(f\"Percentage of Products Ordered:{Percentage_of_Products_Ordered}% \")"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 9, 'mug': 4, 'hat': 11, 'book': 13, 'keychain': 0}\n"
]
}
],
"source": [
"# Update the inventory quantity\n",
"for key in inventory:\n",
" inventory[key]-= 1 # helped by the AI companion here because i don't understand why the code directly deduce 1 to the quantity without precising to work on the value itself\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"For t-shirt product, the updated quantity is:9 kg.\n",
"For mug product, the updated quantity is:4 kg.\n",
"For hat product, the updated quantity is:11 kg.\n",
"For book product, the updated quantity is:13 kg.\n",
"For keychain product, the updated quantity is:0 kg.\n"
]
}
],
"source": [
"for key, value in inventory.items():\n",
" print(f\"For {key} product, the updated quantity is:{value} kg.\")"
]
}
],
"metadata": {
Expand All @@ -68,7 +206,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.9"
}
},
"nbformat": 4,
Expand Down