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Decompose a time series into seasonal, trend, and remainder components. Multiple seasonal periods are allowed. 


AXCEL.DECOMPOSE(data, frequency, start, forecast, [auto], [Report], [plot])

The AXCEL.DECOMPOSE function syntax has the following arguments:

data Required. The time-series data in a column that you would like to decompose. Please note that your data must be a number array. It means that you should not provide a column name in your data.

frequency Required. Frequency of your data. 365 for daily, 52 for weekly, 12 for monthly, and 4 for quarterly data. You can define multiple seasonality, comma-separated. For instance, you can define “12, 4” if you have monthly and quarterly seasonality.

start Required. Start date of your data in “yyyy-mm-dd” format.

auto Optional. By default, no transformation is applied to data. If you set this TRUE, the time series will be Box-Cox transformed before decomposition. 

Report Optional. By default, DECOMPOSE reports Trend, Seasonality, and Remainder. You can define the column name that you need instead of getting the entire columns. For instance, you can define “Trend” to get the trend line only.

plot Optional. default is FALSE. When it is TRUE, Axcel produces the plot inside the sidebar. You can expand the plot and show it in your browser. Here is an example of the plot:

when you type =AXCEL.DECOMPOSE in an Excel cell, the IntelliSense guides you through required and optional (shown in [] brackets) inputs:

In the example above, we have:

=AXCEL.DECOMPOSE(A2:A300, “12, 4”, “1999-3-15”)

This means that our data is located at cells A2 through A300 as an array (column name is not selected), it is monthly but may have quarterly seasonality as well, so the. frequency is set to “12, 4”, it starts from March 15, 1999 (1999-3-15), we do not need Box-Cox transformation and would like Axcel to report all columns by skipping auto and Report for default. Here is the outcome:

As shown, Axcel reports Trend, quarterly and monthly Seasonality and remainders.

Please note that ARIMA function returns dates in Excel format. As a result you may see numbers instead of dates in data_index column. In this case, you need to change the type of column to “Date” from Excel Home menu.