Time Series Forecasting in Python Question

Question

I am trying to understand what is the best possible way to execute a time series forecast. I am trying to forecast the number of employees that are going to call in sick on a given day. My data has the current features.

• Employee hometown
• Job title of employee
• Seniority of employee
• Date
• Day of week
• Week of Year
• Sick count

The Employee hometown, job title, and seniority columns are important because sick numbers historically are heavily dependent on these attributes. Also, I would like to execute an algorithm that also puts a heavier weight on 2021 and 2022 sick counts.

Any ideas would be greatly appreciated!

Answer 1

I assume that sick count is a numerical variable. If so, you could pre-process your data in a way to give a higher value to sick counts for the years $2021$ and $2022$. To make an example, if your sick count for the year $2021$ in the original data is $x = 10$ you could do $5 \cdot x = 50$ to give a higher value on such counts. It is not guaranteed that such a trick will work, but at least you could give it a try as it depends on the forecasting algorithm.