code: def load_adjusted_array(self, domain, columns, dates, sids, mask):
          
          if len(columns) != 1:
              raise ValueError(
                  "Can't load multiple columns with DataFrameLoader"
              )
  
          column = columns[0]
          self._validate_input_column(column)
  
          date_indexer = self.dates.get_indexer(dates)
          assets_indexer = self.assets.get_indexer(sids)
  
          # Boolean arrays with True on matched entries
          good_dates = (date_indexer != -1)
          good_assets = (assets_indexer != -1)
  
          data = self.baseline[ix_(date_indexer, assets_indexer)]
          mask = (good_assets & as_column(good_dates)) & mask
  
          # Mask out requested columns/rows that didn't match.
          data[~mask] = column.missing_value
  
          return {
              column: AdjustedArray(
                  # Pull out requested columns/rows from our baseline data.
                  data=data,
                  adjustments=self.format_adjustments(dates, sids),
                  missing_value=column.missing_value,
              ),
          }
docs: Load data from our stored baseline.