Removing trends in variability via the logarithmic transformation

The logarithmic function log() is a data transformation that can be applied to positively valued time series data. It slightly shrinks observations that are greater than one towards zero, while greatly shrinking very large observations. This property can stabilize variability when a series exhibits increasing variability over time. It may also be used to linearize a rapid growth pattern over time.

The time series rapid_growth has already been loaded, and is shown in the figure on the right. Note the vertical range of the data.

Apply the log() function to rapid_growth, saving the result as linear_growth.
Use ts.plot() to show the transformed series linear_growth and note the condensed vertical range of the transformed data.

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Exercise

Removing trends in variability via the logarithmic transformation

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