ezyquant.reader.SETDataReader.get_data_industry_daily

SETDataReader.get_data_industry_daily(field: str, industry_list: List[str] | None = None, start_date: str | None = None, end_date: str | None = None) → DataFrame

Data from table DAILY_SECTOR_INFO. Filter only industry data.

Parameters:

• field (str) –

  • prior

  • open

  • high

  • low

  • close

  • trans

  • volume

  • value

  • mkt_pe

  • mkt_pbv

  • mkt_yield

  • mkt_cap

  • turnover

  • share_listed_avg

  • beta

  • turnover_volume

  • 12m_dvd_yield

• industry_list (Optional[List[str]] = None) – N_SYMBOL_FEED in industry_list. More industry can be found in ezyquant.fields

• start_date (Optional[str] = None) – start of trade_date (D_TRADE).

• end_date (Optional[str] = None) – end of trade_date (D_TRADE).

Returns:

• industry: str as column

• trade_date: date as index

Return type:

pd.DataFrame

Examples

>>> from ezyquant import SETDataReader
>>> from ezyquant import fields as fld
>>> sdr = SETDataReader()
>>> sdr.get_data_industry_daily(
...     field=fld.D_INDUSTRY_CLOSE,
...     industry_list=[fld.INDUSTRY_AGRO, fld.INDUSTRY_FINCIAL],
...     start_date="2022-01-01",
...     end_date="2022-01-10",
... )
              AGRO  FINCIAL
2022-01-04  485.98   182.10
2022-01-05  484.98   183.50
2022-01-06  482.90   181.39
2022-01-07  484.50   182.81
2022-01-10  487.10   182.79