ezyquant.reader.SETDataReader.get_data_symbol_daily#

SETDataReader.get_data_symbol_daily(field: str, symbol_list: List[str] | None = None, start_date: str | None = None, end_date: str | None = None, adjusted_list: List[str] = ['', 'CR', 'PC', 'RC', 'SD', 'XR']) DataFrame#

Data from table DAILY_STOCK_TRADE, DAILY_STOCK_STAT.

Filter only Auto Matching (I_TRADING_METHOD=’A’).

Parameters:
  • field (str) –

    • prior

    • open

    • high

    • low

    • close

    • average

    • last_bid

    • last_offer

    • trans

    • volume

    • value

    • pe

    • pb

    • par

    • dps

    • dvd_yield

    • mkt_cap

    • eps

    • book_value

    • quarter_fin

    • month_dvd

    • as_of

    • dividend

    • status

    • benefit

    • share_listed

    • turnover

    • share_index

    • npg

    • total_volume

    • total_value

    • beta

    • roi

    • acc_dps

    • dvd_payment

    • dvd_payout

    • earning

    • iv

    • delta

    • notice

    • non_compliance

    • stabilization

    • call_market

    • caution

    • 12m_dvd_yield

    • peg

    • has_trade (if close > 0 or last_bid > 0 or last_offer > 0 return 1.0 else 0.0/nan)

  • symbol_list (Optional[List[str]] = None) – N_SECURITY in symbol_list (must be unique).

  • start_date (Optional[str] = None) – start of trade_date (D_TRADE), by default None

  • end_date (Optional[str] = None) – end of trade_date (D_TRADE), by default None

  • adjusted_list (List[str] = ["", "CR", "PC", "RC", "SD", "XR"]) – Adjust data by ca_type (empty list for no adjustment).

Returns:

  • symbol(N_SECURITY): str as column

  • trade_date(D_TRADE): date as index

Return type:

pd.DataFrame

Warning

  • OHLCV is 0 if no trade.

Examples

>>> from ezyquant import SETDataReader
>>> from ezyquant import fields as fld
>>> sdr = SETDataReader()
>>> sdr.get_data_symbol_daily(
...    field=fld.D_CLOSE,
...    symbol_list=["COM7", "MALEE"],
...    start_date="2022-01-01",
...    end_date="2022-01-10",
... )
              COM7  MALEE
2022-01-04  41.875   6.55
2022-01-05  41.625   6.50
2022-01-06  41.500   6.50
2022-01-07  41.000   6.40
2022-01-10  40.875   6.30