load_linnerud (original) (raw)
sklearn.datasets.load_linnerud(*, return_X_y=False, as_frame=False)[source]#
Load and return the physical exercise Linnerud dataset.
This dataset is suitable for multi-output regression tasks.
Read more in the User Guide.
Parameters:
return_X_ybool, default=False
If True, returns (data, target)
instead of a Bunch object. See below for more information about the data
and target
object.
Added in version 0.18.
as_framebool, 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.
Added in version 0.23.
Returns:
dataBunch
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
andtarget
.
Added 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.
Added 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.
Added in version 0.18.
Examples
from sklearn.datasets import load_linnerud linnerud = load_linnerud() linnerud.data.shape (20, 3) linnerud.target.shape (20, 3)