code: def get_adjustments(self,
                          zero_qtr_data,
                          requested_qtr_data,
                          last_per_qtr,
                          dates,
                          assets,
                          columns,
                          **kwargs):
          
  
          zero_qtr_data.sort_index(inplace=True)
          # Here we want to get the LAST record from each group of records
          # corresponding to a single quarter. This is to ensure that we select
          # the most up-to-date event date in case the event date changes.
          quarter_shifts = zero_qtr_data.groupby(
              level=[SID_FIELD_NAME, NORMALIZED_QUARTERS]
          ).nth(-1)
  
          col_to_all_adjustments = {}
          sid_to_idx = dict(zip(assets, range(len(assets))))
          quarter_shifts.groupby(level=SID_FIELD_NAME).apply(
              self.get_adjustments_for_sid,
              dates,
              requested_qtr_data,
              last_per_qtr,
              sid_to_idx,
              columns,
              col_to_all_adjustments,
              **kwargs
          )
          return col_to_all_adjustments
docs: Creates an AdjustedArray from the given estimates data for the given
          dates.
  
          Parameters
          ----------
          zero_qtr_data : pd.DataFrame
              The 'time zero' data for each calendar date per sid.
          requested_qtr_data : pd.DataFrame
              The requested quarter data for each calendar date per sid.
          last_per_qtr : pd.DataFrame
              A DataFrame with a column MultiIndex of [self.estimates.columns,
              normalized_quarters, sid] that allows easily getting the timeline
              of estimates for a particular sid for a particular quarter.
          dates : pd.DatetimeIndex
              The calendar dates for which estimates data is requested.
          assets : pd.Int64Index
              An index of all the assets from the raw data.
          columns : list of BoundColumn
              The columns for which adjustments need to be calculated.
          kwargs :
              Additional keyword arguments that should be forwarded to
              `get_adjustments_for_sid` and to be used in computing adjustments
              for each sid.
  
          Returns
          -------
          col_to_all_adjustments : dict[int -> AdjustedArray]
              A dictionary of all adjustments that should be applied.