def METHOD_NAME(dataset_url):
    """Prepares a training dataset as pd.DataFrame."""
    csv_file = 'datasets/petfinder-mini/petfinder-mini.csv'
    tf.keras.utils.get_file('petfinder_mini.zip', dataset_url,
                            extract=True, cache_dir='.')
    dataframe = pd.read_csv(csv_file)
    # In the original dataset "4" indicates the pet was not adopted.
    dataframe['target'] = np.where(dataframe['AdoptionSpeed']==4, 0, 1)
    # Drop un-used columns.
    dataframe = dataframe.drop(columns=['AdoptionSpeed', 'Description'])
    return dataframe