Hello, after further investigating the subject, I asked in a telegram group called "Python for trading"

in this group, I managed to find the answer, many thanks to @ultra1971 , he is the one who generated the code and after my question he quickly answered with a valid answer which allows to obtain the quantstats sheet without having to use pyfolio adding modifications in the timeframe in which the backtrader runs. The solution is the next.

First a custom analyzer is created.

class QuantStats(bts.Analyzer):
    """
    Analyzer returning market and bechmark values for report returns to quantstats
    """
    params = (('benchmark', 0),)

    def start(self):
        super().start()

    def create_analysis(self):
        self.rets = {}
        #self.vals = 0.0

    def notify_cashvalue(self, cash, value):
        #self.vals = (value)
        benchmark_value = self.datas[self.p.benchmark].close[0]
        self.rets[self.strategy.datetime.datetime()] = (value, benchmark_value)

    def get_analysis(self):
        return self.rets

Then added to Cerebro.

cerebro.addanalyzer(QuantStats, _name='qs')

thestrats = cerebro.run()
thestrat = thestrats[0]

 returns_analyzer = thestrat.analyzers.getbyname("qs").get_analysis()

 df_qs = pd.DataFrame(returns_analyzer).T
 returns = qs.utils.to_returns(df_qs.iloc[:, 0])
 qs.reports.html(returns,output='test_qs.html', )

Finally, the analyzer data is obtained and the modified returns are added to the sheet.

I hope this helps the community, I had seen many people with these questions and could not find an answer.

Thanks to @ultra1971, who managed to solve the problem and clear up all my doubts, thank you very much!

Hello, after further investigating the subject, I asked in a telegram group called "Python for trading"

in this group, I managed to find the answer, many thanks to @ultra1971 , he is the one who generated the code and after my question he quickly answered with a valid answer which allows to obtain the quantstats sheet without having to use pyfolio adding modifications in the timeframe in which the backtrader runs. The solution is the next.

First a custom analyzer is created.

class QuantStats(bts.Analyzer):
    """
    Analyzer returning market and bechmark values for report returns to quantstats
    """
    params = (('benchmark', 0),)

    def start(self):
        super().start()

    def create_analysis(self):
        self.rets = {}
        #self.vals = 0.0

    def notify_cashvalue(self, cash, value):
        #self.vals = (value)
        benchmark_value = self.datas[self.p.benchmark].close[0]
        self.rets[self.strategy.datetime.datetime()] = (value, benchmark_value)

    def get_analysis(self):
        return self.rets

Then added to Cerebro.

cerebro.addanalyzer(QuantStats, _name='qs')

thestrats = cerebro.run()
thestrat = thestrats[0]

 returns_analyzer = thestrat.analyzers.getbyname("qs").get_analysis()

 df_qs = pd.DataFrame(returns_analyzer).T
 returns = qs.utils.to_returns(df_qs.iloc[:, 0])
 qs.reports.html(returns,output='test_qs.html', )

Finally, the analyzer data is obtained and the modified returns are added to the sheet.

I hope this helps the community, I had seen many people with these questions and could not find an answer.

Thanks to @ultra1971, who managed to solve the problem and clear up all my doubts, thank you very much!