Analyzers stats when datas have only trading days

Hi there,
I'd like to know if the fact that a line has only trading days (i.e 180 days instead of 365) in a year, could affect analyzers calculations such as annualized returns, because something like that would be wrong:dt = st.data._dataname['open'].index bt_period = dt[1]  dt[0] bt_period_days = bt_period.days annual_return_pct = (1 + total_return)**(365.25 / bt_period_days)  100)

I've used different sources of data for stocks and futures, but never seen weekends or holidays included in the data sets. I assume that the standard approach is to skip empty days and keep only trading days.
bt
uses standard number of days (252) for the annualization. 
@ab_trader :
Thanks, yes of course. The example above came from this guy's performance report:
https://github.com/Oxylo/btreport/blob/master/report.py and it relies on ALL the days of the period, just checking on how the builtin analyzers deal with that... 
The calculations above looks correct. Doesn't matter how many trading days you have,
dt[1]  dt[0]
will give you calendar number of days. 
@exu said in Analyzers stats when datas have only trading days:
just checking on how the builtin analyzers deal with that...
I fail to understand what the builtin analyzers have to deal with. They have defacto default values (the ones mostly used by the industry/people/callitX) which you can customize to your liking.