def targetFeatureSplit( data ):
    """
        given a numpy array like the one returned from
        featureFormat, separate out the first feature
        and put it into its own list (this should be the
        quantity you want to predict)

        return targets and features as separate lists

        (sklearn can generally handle both lists and numpy arrays as
        input formats when training/predicting)
        """


    target = []
    features = []
    feature1 = []
    feature2 = []
    # if len(data[0]) <= 2:
    for item in data:
        target.append( item[0] )
        features.append( item[1:] )
    return target, features
    # else:
    #     for item in data:
    #         target.append(item[0])
    #         feature1.append(item[1])
    #         feature2.append(item[2])
    #
    #     return target, feature1, feature2