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# `sklearn.datasets`.load_linnerud

sklearn.datasets.load_linnerud(*, return_X_y=False, as_frame=False)

  Load and return the physical exercise Linnerud dataset.

  This dataset is suitable for multi-output regression tasks.

  Samples total | 20
  Dimensionality | 3 (for both data and target)
  Features | integer
  Targets | integer

  Read more in the User Guide.

  Parameters:
    return_X_y bool, default=False

      If True, returns `(data, target)` instead of a Bunch object. See below for more information about the `data` and `target` object.

      New in version 0.18.

    as_frame bool, default=False

      If True, the data is a pandas DataFrame including columns with appropriate dtypes (numeric, string or categorical). The target is a pandas DataFrame or Series depending on the number of target columns. If `return_X_y` is True, then (`data`, `target`) will be pandas DataFrames or Series as described below.

      New in version 0.23.

  Returns:
    data `Bunch`

      Dictionary-like object, with the following attributes.

      data{ndarray, dataframe} of shape (20, 3)

        The data matrix. If `as_frame=True`, `data` will be a pandas DataFrame.

      target: {ndarray, dataframe} of shape (20, 3)

        The regression targets. If `as_frame=True`, `target` will be a pandas DataFrame.

      feature_names: list

        The names of the dataset columns.

      target_names: list

        The names of the target columns.

      frame: DataFrame of shape (20, 6)

        Only present when `as_frame=True`. DataFrame with `data` and `target`.

        New in version 0.23.

      DESCR: str

        The full description of the dataset.

      data_filename: str

        The path to the location of the data.

      target_filename: str

        The path to the location of the target.

        New in version 0.20.

    (data, target)tuple if `return_X_y` is True

      Returns a tuple of two ndarrays or dataframe of shape `(20, 3)`. Each row represents one sample and each column represents the features in `X` and a target in `y` of a given sample.

      New in version 0.18.