ezyquant.reader.SETDataReader.get_data_sector_daily

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

Data from table DAILY_SECTOR_INFO. Filter only sector 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

• sector_list (Optional[List[str]] = None) – N_SYMBOL_FEED in sector_list. More sector 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:

• sector: 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_sector_daily(
...     field=fld.D_SECTOR_CLOSE,
...     sector_list=[fld.SECTOR_AGRI, fld.SECTOR_BANK],
...     start_date="2022-01-01",
...     end_date="2022-01-10",
... )
              AGRI    BANK
2022-01-04  296.13  421.31
2022-01-05  297.66  423.08
2022-01-06  299.85  417.30
2022-01-07  300.12  421.00
2022-01-10  306.93  423.81