A time series is a collection of data collected in a temporal order, usually used to analyze and predict future trends. According to the distribution characteristics of the data and the purpose of the research, time series can be divided into the following categories: 1. Stationary time series: The data's mean, deviation, and auto-dependence remain unchanged over time. 2. Non-stationary time series: The mean value, variation, and auto-dependence of the data change over time. 3. Seasonal time series: The data has seasonal changes, that is, the same periodic changes occur every year or season. 4. Trending time series: The data shows a linear or non-linear trend change. 5. Compound time series: A time series with both seasonal and trending changes. While waiting for the TV series, you can also click on the link below to read the classic original work of "Dafeng Nightwatchman"!