def get_history_window(self, assets, end_dt, bar_count, frequency, field,
                           data_frequency, ffill=True):
        if frequency == "1d":
            end_idx = \
                self.trading_calendar.all_sessions.searchsorted(end_dt)
            days = self.trading_calendar.all_sessions[
                (end_idx - bar_count + 1):(end_idx + 1)
            ]

            df = pd.DataFrame(
                np.full((bar_count, len(assets)), 100.0),
                index=days,
                columns=assets
            )

            return df