Demos
======================

.. py:module:: evalml.demos

.. autoapi-nested-parse::

   Demo datasets.



Submodules
----------
.. toctree::
   :titlesonly:
   :maxdepth: 1

   breast_cancer/index.rst
   churn/index.rst
   diabetes/index.rst
   fraud/index.rst
   weather/index.rst
   wine/index.rst


Package Contents
----------------



Functions
~~~~~~~~~

.. autoapisummary::
   :nosignatures:

   evalml.demos.load_breast_cancer
   evalml.demos.load_churn
   evalml.demos.load_diabetes
   evalml.demos.load_fraud
   evalml.demos.load_weather
   evalml.demos.load_wine



Contents
~~~~~~~~~~~~~~~~~~~
.. py:function:: load_breast_cancer()

   Load breast cancer dataset. Binary classification problem.

   :returns: X and y
   :rtype: (pd.Dataframe, pd.Series)


.. py:function:: load_churn(n_rows=None, verbose=True)

   Load churn dataset, which can be used for binary classification problems.

   :param n_rows: Number of rows from the dataset to return
   :type n_rows: int
   :param verbose: Whether to print information about features and labels
   :type verbose: bool

   :returns: X and y
   :rtype: (pd.Dataframe, pd.Series)


.. py:function:: load_diabetes()

   Load diabetes dataset. Used for regression problems.

   :returns: X and y
   :rtype: (pd.Dataframe, pd.Series)


.. py:function:: load_fraud(n_rows=None, verbose=True)

   Load credit card fraud dataset.

   The fraud dataset can be used for binary classification problems.

   :param n_rows: Number of rows from the dataset to return
   :type n_rows: int
   :param verbose: Whether to print information about features and labels
   :type verbose: bool

   :returns: X and y
   :rtype: (pd.Dataframe, pd.Series)


.. py:function:: load_weather()

   Load the Australian daily-min-temperatures weather dataset.

   :returns: X and y
   :rtype: (pd.Dataframe, pd.Series)


.. py:function:: load_wine()

   Load wine dataset. Multiclass problem.

   :returns: X and y
   :rtype: (pd.Dataframe, pd.Series)