Stationarity
Most time series modeling depends on the data being stationary. The easiest definition of a stationary time series is that most of its statistical characteristics are all roughly constant over time. For statistical characteristics, the mean, variance, and autocorrelation are most commonly mentioned. For this to be true, we cannot have any trends, that is, data cannot increase monotonically over time. There cannot be long cycles of ups and downs either. If any of these things are true, the mean will change over time and the variance too. There are other more complex mathematical tests, such as the following (Augmented) Dickey-Fuller test. We focus on this test here as it is conveniently available in statsmodels.
The fact is that when ...
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