Demos

Demo datasets.

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()[source]

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)[source]

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()[source]

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)[source]

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()[source]

Load the Australian daily-min-termperatures weather dataset.

Returns

X and y

Return type

(pd.Dataframe, pd.Series)

evalml.demos.load_wine()[source]

Load wine dataset. Multiclass problem.

Returns

X and y

Return type

(pd.Dataframe, pd.Series)