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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 find_group(self, star, starlist):
 """ Find the ids of those stars in ``starlist`` which are at a distance less than ``crit_separation`` from ``star``. Parameters star : `~astropy.table.Row` Star which will be either the head of a cluster or an isolated one. starlist : `~astropy.table.Table` List of star positions. Columns named as ``x_0`` and ``y_0``, which corresponds to the centroid coordinates of the sources, must be provided. Returns ------- Array containing the ids of those stars which are at a distance less than ``crit_separation`` from ``star``. """


        star_distance = np.hypot(star['x_0'] - starlist['x_0'],
                                 star['y_0'] - starlist['y_0'])
        distance_criteria = star_distance < self.crit_separation
        return np.asarray(starlist[distance_criteria]['id'])