Load

Get underlying data

etf.load(symbol: str, start_date: datetime.datetime = datetime.datetime(2019, 9, 19, 15, 38, 2, 731876), interval: int = 1440, end_date: datetime.datetime = datetime.datetime(2022, 9, 23, 15, 38, 2, 731892), prepost: bool = False, source: str = ‘YahooFinance’, iexrange: str = ‘ytd’, weekly: bool = False, monthly: bool = False)

Load a symbol to perform analysis using the string above as a template.

Optional arguments and their descriptions are listed above.

The default source is, yFinance (https://pypi.org/project/yfinance/).
Other sources:
        -   AlphaVantage (https://www.alphavantage.co/documentation/)
        -   IEX Cloud (https://iexcloud.io/docs/api/)
        -   Eod Historical Data (https://eodhistoricaldata.com/financial-apis/)

Please note that certain analytical features are exclusive to the specific source.

To load a symbol from an exchange outside of the NYSE/NASDAQ default, use yFinance as the source and
add the corresponding exchange to the end of the symbol. i.e. ‘BNS.TO’.  Note this may be possible with
other paid sources check their docs.

BNS is a dual-listed stock, there are separate options chains and order books for each listing.
Opportunities for arbitrage may arise from momentary pricing discrepancies between listings
with a dynamic exchange rate as a second order opportunity in ForEx spreads.

Find the full list of supported exchanges here:
https://help.yahoo.com/kb/exchanges-data-providers-yahoo-finance-sln2310.html

Certain analytical features, such as VWAP, require the ticker to be loaded as intraday
using the ‘-i x’ argument.  When encountering this error, simply reload the symbol using
the interval argument. i.e. ‘load -t BNS -s YYYY-MM-DD -i 1 -p’ loads one-minute intervals,
including Pre/After Market data, using the default source, yFinance.

Certain features, such as the Prediction menu, require the symbol to be loaded as daily and not intraday.

Parameters
----------
symbol: str
    Ticker to get data
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

Returns
-------
df_stock_candidate: pd.DataFrame
    Dataframe of data