Course Content
Time Series Essentials
Rolling
The rolling
method in Python is used to create a rolling
window
of a certain size on a time series or other data. It takes one or more parameters: the window size, and optionally the type of window (e.g. boxcar, hamming, etc.). It returns a new object that behaves like a moving window on the original data. You can then perform various operations on this windowed data, such as calculating the mean, sum, or standard deviation.
Methods description
rolling(window)
: This method creates a Rolling object that represents a rolling window calculation over the DataFrame. Thewindow
parameter specifies the size of the rolling window;mean()
: This method calculates the mean value over the rolling window. It returns a new DataFrame containing the rolling mean values;print(df)
: This function prints the rolling mean DataFrame to the console.
Swipe to show code editor
- Create a
rolling window
of size3
. - Calculate the
rolling_mean
. - Print the variable.
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The rolling
method in Python is used to create a rolling
window
of a certain size on a time series or other data. It takes one or more parameters: the window size, and optionally the type of window (e.g. boxcar, hamming, etc.). It returns a new object that behaves like a moving window on the original data. You can then perform various operations on this windowed data, such as calculating the mean, sum, or standard deviation.
Methods description
rolling(window)
: This method creates a Rolling object that represents a rolling window calculation over the DataFrame. Thewindow
parameter specifies the size of the rolling window;mean()
: This method calculates the mean value over the rolling window. It returns a new DataFrame containing the rolling mean values;print(df)
: This function prints the rolling mean DataFrame to the console.
Swipe to show code editor
- Create a
rolling window
of size3
. - Calculate the
rolling_mean
. - Print the variable.