figure - web site visits per day time series components the time series at hand is data related to web site visits per day for given web site as mentioned earliertime series analysis deals with understanding the underlying structure and forces that result in the series as we see it let' now try to deconstruct various components that make up the time series at hand time series is said to be comprised of the following three major componentsseasonalitythese are the periodic fluctuations in the observed data for exampleweather patterns or sale patterns trendthis is the increasing or decreasing behavior of the series with time for examplepopulation growth patterns residualthis is the remaining signal after removing the seasonality and trend signals it can be further decomposed to remove the noise component as well it is interesting to note that most real-world time series data have combination or all of these components available yetit is mostly the noise that' always apparently presentwith trend and seasonality being optional in certain cases in the following snippetwe utilize statsmodels to decompose our web site visit time series into its three constituents and then plot the same in [ from statsmodels tsa seasonal import seasonal_decompose extract visits as series from the dataframe ts_visits pd series(input_df visits values