Product Trend Analysis Project with Python

"""Analyse product revenue, share, and year-over-year trends."""

from __future__ import annotations

import numpy as np
import pandas as pd


def make_demo_product_sales(seed: int = 42) -> pd.DataFrame:
    rng = np.random.default_rng(seed)
    months = pd.date_range("2024-01-01", "2025-12-01", freq="MS")
    products = ["Alpha", "Beta", "Gamma", "Delta"]
    rows = []
    for p_index, product in enumerate(products):
        for index, month in enumerate(months):
            base = (85_000 + p_index * 18_000) * (1 + (0.018 - p_index * 0.003) * index)
            rows.append((month, product, max(base + rng.normal(0, 7_000), 0)))
    return pd.DataFrame(rows, columns=["month", "product", "revenue"])


def analyse_products(data: pd.DataFrame) -> tuple[pd.DataFrame, pd.DataFrame]:
    monthly = data.copy().sort_values(["product", "month"])
    monthly["revenue_previous_year"] = monthly.groupby("product")["revenue"].shift(12)
    monthly["yoy_growth"] = monthly["revenue"] / monthly["revenue_previous_year"] - 1
    monthly["month_total"] = monthly.groupby("month")["revenue"].transform("sum")
    monthly["revenue_share"] = monthly["revenue"] / monthly["month_total"]
    latest_month = monthly["month"].max()
    latest = monthly[monthly["month"] == latest_month].sort_values("yoy_growth", ascending=False)
    return monthly, latest[["product", "revenue", "revenue_share", "yoy_growth"]]


def main() -> None:
    _, latest = analyse_products(make_demo_product_sales())
    print(latest.round(3).to_string(index=False))
    print("Year-over-year growth controls for seasonality but does not explain the cause of change.")


if __name__ == "__main__":
    main()