Suppose you are trying to measure if the seasonality of a particular event stream is consistent i.e. the events in a time series happen more or less in pattern like fashion. How can you algorithmically measure and extract seasonality?

Currently, I am using autocorrelation to view the clearly seasonal (monthly) data events. I am struggling to figure out how to write an algorithm that could test whether or not something is seasonal by month. The picture below shows the results of the pacf function within the statsmodels.tsa.stattools library. From the graph it is clear, how can I use the array to determine seasonality? Is there a library that would be useful for this?

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This question is similar, but did not get any great answers: https://stats.stackexchange.com/questions/225003/test-for-trend-and-seasonality-in-time-series

  • $\begingroup$ Stupid question: why don‘t you run a linear model with monthly dummies? This should help to identify monthly patterns. $\endgroup$ – Peter Jan 4 '20 at 13:14

You can try FBProphet for your timeseries analysis. You will be able to check the seasonality, stationarity on your data.


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