Please explain 'self.data0' and 'self.data1' in detail

Could anyone please explain to me the concept of self.data0 and self.data1?
I am trying to understand by reading documents but it seems not quite clear to me on how the values are construct and how can we use them.I would like to use bt.indicators.OLS_Slope_InterceptN which it seems that it needs both variables.
Thank you.

Member Attributes datas: array of data feeds which have been passed to cerebro  data/data0 is an alias for datas[0]  dataX is an alias for datas[X]

Thank you for your information.
Could you please have a look on how we can pass data to this indicator?
For example, if we load Yahoo 'AAPL' data and want to find the slope and intercept.Thank you.
========================================================
class OLS_Slope_InterceptN(PeriodN):
'''
Calculates a linear regression usingstatsmodel.OLS
(Ordinary least
squares) of data1 on data0
Usespandas
andstatsmodels
Useprepend_constant
to influence the paramterprepend
of
sm.add_constant
'''
_mindatas = 2 # ensure at least 2 data feeds are passedpackages = ( ('pandas', 'pd'), ('statsmodels.api', 'sm'), ) lines = ('slope', 'intercept',) params = ( ('period', 10), ('prepend_constant', True), ) def next(self): p0 = pd.Series(self.data0.get(size=self.p.period)) p1 = pd.Series(self.data1.get(size=self.p.period)) p1 = sm.add_constant(p1, prepend=prepend_constant) slope, intercept = sm.OLS(p0, p1).fit().params self.lines.slope[0] = slope self.lines.intercept[0] = intercept

There has been a discussion on this just 2 days ago:

Thank you @PaskaHouso for your actively help.