code: def prior_predictive_to_xarray(self):
          
          prior_predictive = self.prior_predictive
  
          if (
              isinstance(prior_predictive, (tuple, list)) and prior_predictive[0].endswith(".csv")
          ) or (isinstance(prior_predictive, str) and prior_predictive.endswith(".csv")):
              if isinstance(prior_predictive, str):
                  prior_predictive = [prior_predictive]
              chain_data = []
              for path in prior_predictive:
                  parsed_output = _read_output(path)
                  for sample, *_ in parsed_output:
                      chain_data.append(sample)
              data = _unpack_dataframes(chain_data)
          else:
              if isinstance(prior_predictive, str):
                  prior_predictive = [prior_predictive]
              prior_predictive_cols = [
                  col
                  for col in self.prior[0].columns
                  if any(item == col.split(".")[0] for item in prior_predictive)
              ]
              data = _unpack_dataframes([item[prior_predictive_cols] for item in self.prior])
          return dict_to_dataset(data, coords=self.coords, dims=self.dims)
docs: Convert prior_predictive samples to xarray.