It seems that the dataset does not have enough data to compute initial seasonals using the heuristic method. This error occurs because the seasonal period specified is too long for the given data.

Let's try a different approach by using a shorter seasonal period or a different model. I will use a seasonal period of 7 days (weekly seasonality) and fit the model again.

It seems that the dataset does not have enough data to compute initial seasonals using the heuristic method even with a weekly seasonal period. This error occurs because the seasonal period specified is still too long for the given data.

Let's try a different approach by using a simpler model without seasonality.

It seems that the dataset does not have enough data to compute initial seasonals using the heuristic method even with a weekly seasonal period. This error occurs because the seasonal period specified is still too long for the given data.

Let's try a different approach by using a simpler model without seasonality.

The dataset provided does not have enough data to compute initial seasonals using the heuristic method, which caused errors when trying to fit the Exponential Smoothing model with seasonality.

To proceed, we can use a simpler model without seasonality or consider other time series forecasting methods such as ARIMA or Prophet.

Would you like to try a different model or approach for forecasting?