Dj:ddlZddlmZddlmZdgZdZdefd Zy) N)DTYPE)fetch_from_web_or_disk load_gasolinez,http://alkaline-ml.com/datasets/gasoline.csvFcvttddj|}|s|Stj|S)a.Weekly US finished motor gasoline products A weekly time series of US finished motor gasoline products supplied (in thousands of barrels per day) from February 1991 to May 2005. Parameters ---------- as_series : bool, optional (default=False) Whether to return a Pandas series. If True, the index will be set to the observed years/months. 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. Notes ----- The seasonal periodicity of this example is rather difficult, since it's not an integer. To be exact, the periodicity is ``365.25 / 7`` (~=52.1785714285714). To fit the best possible model to this data, you'll need to explore using exogenous features See Also -------- :class:`pmdarima.preprocessing.exog.FourierFeaturizer` Examples -------- >>> from pmdarima.datasets import load_gasoline >>> load_gasoline() array([6621. , 6433. , 6582. , ..., 9024. , 9175. , 9269. ]) >>> load_gasoline(True).head() 0 6621.0 1 6433.0 2 6582.0 3 7224.0 4 6875.0 dtype: float64 References ---------- .. [1] http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=wgfupus2&f=W .. [2] https://robjhyndman.com/hyndsight/forecasting-weekly-data/ Returns ------- rslt : array-like, shape=(n_samples,) The gasoline dataset. There are 745 examples. gasolineT)cache)rurlastypepdSeries) as_seriesdtyperslts ^C:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\pmdarima/datasets/gasoline.pyrrs4f "#z > E Ee LD  99T?) pandasr compat.numpyr_baser__all__r rrrrs/ ) 5"7r