sktime.datasets.base
.load_uschange¶
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sktime.datasets.base.
load_uschange
(y_name='Consumption')[source]¶ Load the multivariate time series dataset for forecasting Growth rates of personal consumption and personal income.
- Returns
y (pandas Series) – selected column, default consumption
X (pandas Dataframe) – columns with explanatory variables
Details
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Percentage changes in quarterly personal consumption expenditure,
personal disposable income, production, savings and the
unemployment rate for the US, 1960 to 2016.
Dimensionality: multivariate Columns: [‘Quarter’, ‘Consumption’, ‘Income’, ‘Production’,
‘Savings’, ‘Unemployment’]
Series length: 188 Frequency: Quarterly Number of cases: 1
Notes
This data shows an increasing trend, non-constant (increasing) variance and periodic, seasonal patterns.
References
..fpp2: Data for “Forecasting: Principles and Practice” (2nd Edition)