<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def point_consensus(self, consensus_type):
 """ Calculate grid-point statistics across ensemble members. Args: consensus_type: mean, std, median, max, or percentile_nn Returns: EnsembleConsensus containing point statistic """

        if "mean" in consensus_type:
            consensus_data = np.mean(self.data, axis=0)
        elif "std" in consensus_type:
            consensus_data = np.std(self.data, axis=0)
        elif "median" in consensus_type:
            consensus_data = np.median(self.data, axis=0)
        elif "max" in consensus_type:
            consensus_data = np.max(self.data, axis=0)
        elif "percentile" in consensus_type:
            percentile = int(consensus_type.split("_")[1])
            consensus_data = np.percentile(self.data, percentile, axis=0)
        else:
            consensus_data = np.zeros(self.data.shape[1:])
        consensus = EnsembleConsensus(consensus_data, consensus_type, self.ensemble_name,
                                      self.run_date, self.variable, self.start_date, self.end_date, self.units)
        return consensus