pmdarima.datasets.load_taylor¶
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pmdarima.datasets.load_taylor(as_series=False, dtype=<class 'numpy.float64'>)[source][source]¶
- Half-hourly electricity demand - Half-hourly electricity demand in England and Wales from Monday, 5 June, 2000 to Sunday, 27 August, 2000. Discussed in Taylor (2003), and kindly provided by James W Taylor. Units: Megawatts - Parameters: - as_series : bool, optional (default=False) - Whether to return a Pandas series. If True, the index will be set to the observed years. If False, will return a 1d numpy array. - dtype : type, optional (default=np.float64) - The type to return for the array. Default is np.float64, which is used throughout the package as the default type. - Returns: - taylor : array-like, shape=(n_samples,) - The Taylor dataset. There are 4032 observations. - Notes - This is annual data and not seasonal in nature (i.e., \(m=1\)) - References - [R81] - Taylor, J.W. (2003) Short-term electricity demand forecasting using double seasonal exponential smoothing. Journal of the Operational Research Society, 54, 799-805. - [R82] - https://www.rdocumentation.org/packages/forecast/versions/8.9/topics/taylor - Examples - >>> from pmdarima.datasets import load_taylor >>> load_taylor()[:10] array([22262., 21756., 22247., 22759., 22549., 22313., 22128., 21860., 21751., 21336.]) - >>> load_taylor(True).head() 0 22262.0 1 21756.0 2 22247.0 3 22759.0 4 22549.0 dtype: float64