.. currentmodule:: sklearn.datasets

The sklearn.datasets package embeds some small toy datasets and provides helpers to fetch larger datasets commonly used by the machine learning community to benchmark algorithms on data that comes from the 'real world'.

To evaluate the impact of the scale of the dataset (n_samples and n_features) while controlling the statistical properties of the data (typically the correlation and informativeness of the features), it is also possible to generate synthetic data.

General dataset API. There are three main kinds of dataset interfaces that can be used to get datasets depending on the desired type of dataset.

The dataset loaders. They can be used to load small standard datasets, described in the :ref:`toy_datasets` section.

The dataset fetchers. They can be used to download and load larger datasets, described in the :ref:`real_world_datasets` section.

Both loaders and fetchers functions return a :class:`~sklearn.utils.Bunch` object holding at least two items: an array of shape n_samples * n_features with key data (except for 20newsgroups) and a numpy array of length n_samples, containing the target values, with key target.

The Bunch object is a dictionary that exposes its keys as attributes. For more information about Bunch object, see :class:`~sklearn.utils.Bunch`.

It's also possible for almost all of these function to constrain the output to be a tuple containing only the data and the target, by setting the return_X_y parameter to True.

The datasets also contain a full description in their DESCR attribute and some contain feature_names and target_names. See the dataset descriptions below for details.

The dataset generation functions. They can be used to generate controlled synthetic datasets, described in the :ref:`sample_generators` section.

These functions return a tuple (X, y) consisting of a n_samples * n_features numpy array X and an array of length n_samples containing the targets y.

In addition, there are also miscellaneous tools to load datasets of other formats or from other locations, described in the :ref:`loading_other_datasets` section.

.. toctree::
    :maxdepth: 2

    datasets/toy_dataset
    datasets/real_world
    datasets/sample_generators
    datasets/loading_other_datasets