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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def hepatitis(return_X_y=True):
 """hepatitis in Bulgaria dataset Parameters return_X_y : bool, if True, returns a model-ready tuple of data (X, y) otherwise, returns a Pandas DataFrame Returns ------- model-ready tuple of data (X, y) OR Pandas DataFrame Notes ----- X contains the age of each patient group. y contains the ratio of HAV positive patients to the total number for each age group. Groups with 0 total patients are excluded. Source: Keiding, N. (1991) Age-specific incidence and prevalence: a statistical perspective """

    # y is real
    # recommend LinearGAM
    hep = pd.read_csv(PATH + '/hepatitis_A_bulgaria.csv').astype(float)
    if return_X_y:
        # eliminate 0/0
        mask = (hep.total > 0).values
        hep = hep[mask]

        X = hep.age.values
        y = hep.hepatitis_A_positive.values / hep.total.values
        return _clean_X_y(X, y)
    return hep