summary_MkTdata¶
Summary of market data time-series length and quality Checks for missing records.
- azapy.MkT.summary_MkTdata.summary_MkTdata(mktdata, calendar=None, sdate=None, edate=None)¶
Summary of MkT data time-series length and quality (checks for missing records).
- Parameters:
- mktdatapandas.DataFrame or a dict of pandas.DataFrame
Market Data in the format returned by azapy.readMkT function.
- calendarstr or numpy.busdaycalendar, optional
Business calendar. It can be the exchange calendar name as a str or a numpy.busdaycalendar object. If it is None then it will be set to NYSE business calendar. The default value is None.
- sdatedate like, optional
Time-series start date. If it is None then sdate will be set to the earliest date in mktdata. The default is None.
- edatedate like, optional
Time-series end date. If it is None then edate will be set to the most recent date in mktdata. The default is None.
- Returns:
- `pandas.DataFrame`A table with columns:
symbol : time-series symbol
begin : start date
end : end date
length : number of records
na_total : total number of nan
na_b : number of missing records at the beginning
na_e : number of missing records at the end
cont : total number of missing records
Notes
Its main application is to assess the missing data in the time-series extracted with azapy.readMkT function.