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Deseasonalization of data refers to the process of removing seasonal effects from a time series to reveal underlying trends and patterns. This is typically done by calculating and subtracting seasonal averages or indices from the original data, allowing for a clearer analysis of non-seasonal components. By deseasonalizing data, analysts can better understand the true behavior of the data over time, making it easier to forecast future values without the influence of seasonal fluctuations.

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