load_covid_3month¶

load_covid_3month(split=None, return_type='numpy3d')[source]¶

Load dataset of last three months confirmed covid cases.

Parameters:

split: None or str{“train”, “test”}, default=None: Whether to load the train or test partition of the problem. By default, it loads both.
return_type: string, default=”numpy3d”: Data structure to use for time series, should be either “numpy2d” or “numpy3d”.

Returns:

X: np.ndarray: The time series data.
y: np.ndarray: The regression values for each case in X.

Notes

Dimensionality: univariate Series length: 84 Train cases: 140 Test cases: 61 Number of classes: -

The goal of this dataset is to predict COVID-19’s death rate on 1st April 2020 for each country using daily confirmed cases for the last three months. This dataset contains 201 time series with no missing values, where each time series is the daily confirmed cases for a country. The data was obtained from WHO’s COVID-19 database. Please refer to https://covid19.who.int/ for more details

Dataset details: https://zenodo.org/record/3902690#.Yy1z_HZBxEY =Covid3Month

Examples

>>> from aeon.datasets import load_covid_3month
>>> X, y = load_covid_3month()