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

# Create revenue column
df["revenue"] = df["quantity"] * df["price"]

# Filter orders from 2023 onwards
df_filtered = df[df["order_date"] >= "2023-01-01"]

# Convert order_date and extract month
df_filtered["month"] = pd.to_datetime(df_filtered["order_date"]).dt.to_period("M")

# Group by category and month, then sum revenue
grouped = df_filtered.groupby(["category", "month"])["revenue"].sum()

# Convert to DataFrame
result = grouped.reset_index()

# Sort results
result = result.sort_values(by="revenue", ascending=False)