'Parameters
group : pd.DataFrame
The data for the given sid.
dates : pd.DatetimeIndex
The calendar dates for which estimates data is requested.
requested_qtr_data : pd.DataFrame
The DataFrame with the latest values for the requested quarter
for all columns.
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.
sid_to_idx : dict[int -> int]
A dictionary mapping sid to he sid\'s index in the asset index.
columns : list of BoundColumn
The columns for which the overwrites should be computed.
col_to_all_adjustments : dict[int -> AdjustedArray]
A dictionary of the integer index of each timestamp into the date
index, mapped to adjustments that should be applied at that
index. This dictionary is for adjustments for ALL sids. It is
modified as adjustments are collected.
kwargs :
Additional arguments used in collecting adjustments; unused here.'

def get_adjustments_for_sid(self, group, dates, requested_qtr_data, last_per_qtr, sid_to_idx, columns, col_to_all_adjustments, **kwargs):

    all_adjustments_for_sid = {}
    sid = int(group.name)
    self.collect_overwrites_for_sid(group, dates, requested_qtr_data, last_per_qtr, sid_to_idx[sid], columns, all_adjustments_for_sid, sid)
    self.merge_into_adjustments_for_all_sids(all_adjustments_for_sid, col_to_all_adjustments)
