import pandas as pd

df = pd.DataFrame(
    {
        "item": ["notebook", "pencil", "eraser"],
        "qty": [3, 10, 5],
        "unit_price": [2.5, 0.4, 0.8],
    }
)

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

print("BASE")
print(df)
print()

df["line_total"] = df["qty"] * df["unit_price"]

print("LINE_TOTAL")
print(df)
print()

df["currency"] = "USD"

print("CURRENCY")
currency_cols = ["item", "line_total", "currency"]
print(df[currency_cols])
print()

df["bulk_order"] = False

print("BULK_DEFAULT")
bulk_cols = ["item", "qty", "bulk_order"]
print(df[bulk_cols])
print()

df.loc[df["qty"] >= 10, "bulk_order"] = True

print("BULK_LOC")
print(df[bulk_cols])
print()

result = df.assign(
    discount=lambda data: (data["line_total"] * 0.10).where(data["bulk_order"], 0),
    net_total=lambda data: data["line_total"] - data["discount"],
)

print("ASSIGN")
summary_cols = ["item", "line_total", "discount", "net_total"]
print(result[summary_cols])
print()

result.insert(1, "sku", ["N-100", "P-200", "E-300"])

print("INSERT")
insert_cols = ["item", "sku", "qty", "line_total", "net_total"]
print(result[insert_cols])
print()

print("VERIFY_COLUMNS")
print(result.columns.tolist())
print()

print("VERIFY_DTYPES")
dtype_cols = ["line_total", "bulk_order", "net_total"]
print(result[dtype_cols].dtypes)