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.

calendarnumpy.busdaycalendar, optional

Business days calendar. If is set to None it will default to NYSE business calendar.

sdatepandas.Timestamp, optional

Time-series start date. If it is None then sdate will be set to the earliest date in mktdata. The default is None.

edatepandas.Timestamp, 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.

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Example update_MkTdata

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