df = pd.read_csv("sales.csv")  # Load dataset

# Create new columns upfront
df["revenue"] = df["quantity"] * df["price"]
df["month"] = pd.to_datetime(df["order_date"]).dt.to_period("M")

result = (
    # Filter relevant rows
    df[df["order_date"] >= "2023-01-01"]
    
    # Aggregate revenue by category and month
    .groupby(["category", "month"])["revenue"]
    .sum()
    
    # Convert to DataFrame
    .reset_index()
    
    # Sort results
    .sort_values(by="revenue", ascending=False)
)