import pandas as pd

orders = pd.DataFrame(
    {
        "order_id": [1001, 1002, 1003, 1004, 1005, 1006],
        "customer": ["Ada", "Lin", "Maya", "Omar", "Nia", "Kai"],
        "region": ["EMEA", "APAC", "AMER", "EMEA", "APAC", "AMER"],
        "category": ["hardware", "software", "hardware", "service", "software", "hardware"],
        "qty": [3, 12, 7, 2, 15, 9],
        "total_usd": [150.0, 240.0, 875.0, 95.0, 360.0, 420.0],
        "status": ["paid", "paid", "open", "paid", "open", "paid"],
    }
)

print(f"pandas {pd.__version__}")
print()

print("BASE")
print(orders.to_string(index=False))
print()

high_value = orders.loc[
    orders["total_usd"] >= 300,
    ["order_id", "customer", "region", "total_usd"],
]

print("FILTER_TOTAL")
print(high_value.to_string(index=False))
print()

regions = ["EMEA", "APAC"]
priority_mask = (orders["region"].isin(regions)) & (orders["qty"] >= 10)
priority = orders.loc[
    priority_mask,
    ["order_id", "customer", "region", "qty", "total_usd"],
]

print("FILTER_REGION_QTY")
print(priority.to_string(index=False))
print()

paid_hardware = orders.loc[
    (orders["status"] == "paid") & (orders["category"] == "hardware"),
    ["order_id", "customer", "category", "status", "total_usd"],
]

print("FILTER_STATUS_CATEGORY")
print(paid_hardware.to_string(index=False))
print()

customer_match = orders.loc[
    orders["customer"].str.contains("a", case=False, regex=False, na=False),
    ["order_id", "customer", "region"],
]

print("FILTER_CUSTOMER_TEXT")
print(customer_match.to_string(index=False))
print()

print("VERIFY")
print(f"priority rows: {len(priority)}")
print(f"priority index: {priority.index.tolist()}")
print(f"all priority qty >= 10: {priority['qty'].ge(10).all()}")
print(f"source rows unchanged: {len(orders)}")