Time series analysis is a powerful tool for understanding and predicting trends in data that changes over time. However, there are several pitfalls that can lead to inaccurate results and misleading conclusions. In this blog post, we'll discuss some of the most common pitfalls in time series analysis, including non-stationary data, the need for careful data preprocessing, and the use of inappropriate methods or models. We'll also provide tips for avoiding these pitfalls and ensuring the reliability of your time series analysis. By understanding and addressing these challenges, you can improve the accuracy and usefulness of your time series analysis. Those are the top 5 pitfalls: