Challenge: Forecast and Replenish

Before you tackle a full challenge, it's important to recap the key concepts you'll need. Moving average forecasting is a simple but powerful technique where you predict future demand by averaging actual demand over a fixed window of previous days. This helps smooth out fluctuations and provides a reasonable short-term forecast. In inventory simulation, you track how stock levels change over time, considering daily demand and replenishment rules. A common approach is to set a reorder point: when inventory drops below this threshold, you replenish up to a desired level. By combining forecasting and inventory simulation, you can better anticipate stockouts and optimize replenishment decisions.

For this challenge, you will use the provided daily demand list and inventory parameters to build a complete forecasting and inventory management workflow. Start by implementing a moving average forecast using the specified window size. For each day after the initial window, calculate the average of the preceding days to produce the forecasted demand. Next, simulate inventory levels: begin with the initial stock, subtract daily demand, and whenever the inventory falls below the reorder point, replenish by the fixed quantity. The reorder point should be calculated as the average demand over the moving average window, multiplied by the window size. Throughout the 30-day period, keep track of both actual and forecasted demand, inventory levels, and any days when a stockout (inventory dropping below zero) occurs. Finally, visualize the actual and forecasted demand as well as the inventory levels on a line plot, and print a summary listing all days when stockouts happened.