Demos

Demo datasets.

Submodules

• breast_cancer
• churn
• diabetes
• fraud
• weather
• wine

Package Contents

Functions

load_breast_cancer	Load breast cancer dataset. Binary classification problem.
load_churn	Load churn dataset, which can be used for binary classification problems.
load_diabetes	Load diabetes dataset. Used for regression problem.
load_fraud	Load credit card fraud dataset.
load_weather	Load the Australian daily-min-termperatures weather dataset.
load_wine	Load wine dataset. Multiclass problem.

Contents

evalml.demos.load_breast_cancer()

Load breast cancer dataset. Binary classification problem.

Returns

X and y

Return type

(pd.Dataframe, pd.Series)

evalml.demos.load_churn(n_rows=None, verbose=True)

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

Parameters

• n_rows (int) – Number of rows from the dataset to return

• verbose (bool) – Whether to print information about features and labels

Returns

X and y

Return type

(pd.Dataframe, pd.Series)

evalml.demos.load_diabetes()

Load diabetes dataset. Used for regression problem.

Returns

X and y

Return type

(pd.Dataframe, pd.Series)

evalml.demos.load_fraud(n_rows=None, verbose=True)

Load credit card fraud dataset.

The fraud dataset can be used for binary classification problems.

Parameters

• n_rows (int) – Number of rows from the dataset to return

• verbose (bool) – Whether to print information about features and labels

Returns

X and y

Return type

(pd.Dataframe, pd.Series)

evalml.demos.load_weather()

Load the Australian daily-min-termperatures weather dataset.

Returns

X and y

Return type

(pd.Dataframe, pd.Series)

evalml.demos.load_wine()

Load wine dataset. Multiclass problem.

Returns

X and y

Return type

(pd.Dataframe, pd.Series)

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