# Let us start by making a simple list of sales amounts
sales = [20.0, 35.5, 12.0, 46.0, 28.75]
print(sales)  # This will show our sales data

# How many sales did we record?
num_sales = len(sales)
print(num_sales)

# What was the total amount of all sales?
total_sales = sum(sales)
print(total_sales)

# Let us find the average sale amount
average_sale = total_sales / num_sales
print(average_sale)

# Creating a sale as a dictionary: it holds details in key-value pairs
sale1 = {'customer': 'Alice', 'item': 'Book', 'amount': 20.0}
print(sale1)

# Let us create a list of dictionaries for multiple sales
sales_records = [
    {'customer': 'Alice', 'item': 'Book', 'amount': 20.0},
    {'customer': 'Bob', 'item': 'Pen', 'amount': 5.0},
    {'customer': 'Carol', 'item': 'Notebook', 'amount': 15.5},
    {'customer': 'Dan', 'item': 'Bag', 'amount': 45.0}
]
print(sales_records)

# Let us loop through sales and print each one nicely
for sale in sales_records:
    print(f"Customer: {sale['customer']} bought {sale['item']} for ${sale['amount']}")
    

# Calculate the total sales amount from all records
total = 0
for sale in sales_records:
    total += sale['amount']
print(total)

# What if a customer returns an item? Let us remove that sale by index.
returned_index = 1  # Suppose Bob returned the pen.
del sales_records[returned_index]
print(sales_records)

# Let us safely access a key even if it might not exist
if 'coupon' in sales_records[0]:
    print(sales_records[0]['coupon'])
else:
    print("No coupon used!")
    

# Update a sale to record that a coupon was used
sales_records[0]['coupon'] = 'SUMMER20'
print(sales_records[0])

# Let us filter the sales to find only those above $20
big_sales = []
for sale in sales_records:
    if sale['amount'] > 20:
        big_sales.append(sale)
print(big_sales)

# Using list comprehensions to find all customer names
customer_names = [sale['customer'] for sale in sales_records]
print(customer_names)

# Let us ask the user to add a new sale
customer = input('Customer name: ')
item = input('Item: ')
amount = float(input('Amount: '))
new_sale = {'customer': customer, 'item': item, 'amount': amount}
sales_records.append(new_sale)
print(sales_records)

# Sort sales by amount, from highest to lowest
sorted_sales = sorted(sales_records, key=lambda x: x['amount'], reverse=True)
for sale in sorted_sales:
    print(f"{sale['customer']} spent ${sale['amount']} on a {sale['item']}")
    

# Let us combine all sales amounts to get a daily summary
daily_total = sum([sale['amount'] for sale in sales_records])
print(f"Total sales for the day: ${daily_total}")

# Let us make a small report showing customers and totals spent
totals = {}
for sale in sales_records:
    name = sale['customer']
    if name in totals:
        totals[name] += sale['amount']
    else:
        totals[name] = sale['amount']
for name, total in totals.items():
    print(f"{name}: ${total}")
    

# Let us handle the case where a customer might not be in the report
name = input('Enter a customer name to check total: ')
if name in totals:
    print(f"{name} spent ${totals[name]}")
else:
    print(f"No record for {name}")
    

# Mini Project, Part 1: Gather a few sales from the user
my_sales = []
for i in range(3):
    print(f"Enter info for sale {i+1}:")
    customer = input('Customer name: ')
    item = input('Item: ')
    amount = float(input('Amount: '))
    my_sales.append({'customer': customer, 'item': item, 'amount': amount})
print(my_sales)

# Mini Project, Part 2: Report stats and biggest sale
amounts = [sale['amount'] for sale in my_sales]
if amounts:
    print(f"Total sales: ${sum(amounts)}")
    print(f"Average sale: ${sum(amounts)/len(amounts):.2f}")
    max_sale = max(my_sales, key=lambda x: x['amount'])
    print(f"Biggest sale: {max_sale['customer']} bought a {max_sale['item']} for ${max_sale['amount']}")
else:
    print("No sales recorded.")
    

# Some tips for clean and safe data analysis!
# - Always check your data types.
# - Use try-except to handle unexpected input or errors.
# - Keep your code neat and comment important steps.
# - Test using both normal and weird data.

print("Tip: Small, clear changes make bugs easier to fix!")

# Common mistakes in sales data analysis
try:
    problem = float('twenty')  # This will not work!
except ValueError:
    print("Oops, be sure inputs are numbers!")