Candle

Get underlying data

etf.candle(symbol: str, data: pandas.core.frame.DataFrame = None, use_matplotlib: bool = True, intraday: bool = False, add_trend: bool = False, ma: Optional[Iterable[int]] = None, asset_type: str = ‘’, start_date: datetime.datetime = datetime.datetime(2019, 9, 19, 15, 38, 2, 731895), interval: int = 1440, end_date: datetime.datetime = datetime.datetime(2022, 9, 23, 15, 38, 2, 731896), prepost: bool = False, source: str = ‘YahooFinance’, iexrange: str = ‘ytd’, weekly: bool = False, monthly: bool = False, external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None, raw: bool = False)

Shows candle plot of loaded ticker. [Source: Yahoo Finance, IEX Cloud or Alpha Vantage]

Parameters
----------
symbol: str
    Ticker name
data: pd.DataFrame
    Stock dataframe
use_matplotlib: bool
    Flag to use matplotlib instead of interactive plotly chart
intraday: bool
    Flag for intraday data for plotly range breaks
add_trend: bool
    Flag to add high and low trends to chart
ma: Tuple[int]
    Moving averages to add to the candle
asset_type_: str
    String to include in title
external_axes : Optional[List[plt.Axes]], optional
    External axes (2 axes are expected in the list), by default None
asset_type_: str
    String to include in title
start_date: datetime
    Start date to get data from with
interval: int
    Interval (in minutes) to get data 1, 5, 15, 30, 60 or 1440
end_date: datetime
    End date to get data from with
prepost: bool
    Pre and After hours data
source: str
    Source of data extracted
iexrange: str
    Timeframe to get IEX data.
weekly: bool
    Flag to get weekly data
monthly: bool
    Flag to get monthly data
raw : bool, optional
    Flag to display raw data, by default False