load_uschange#
- load_uschange(y_name='Consumption')[source]#
Load MTS dataset for forecasting Growth rates of personal consumption and income.
- Returns:
- ypd.Series
selected column, default consumption
- Xpd.DataFrame
columns with explanatory variables
Notes
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
This data shows an increasing trend, non-constant (increasing) variance and periodic, seasonal patterns.
References
[1]Data for “Forecasting: Principles and Practice” (2nd Edition)
Examples
>>> from sktime.datasets import load_uschange >>> y, X = load_uschange()