Tickers

download()

Fetch price data for many tickers from Yahoo and make user-friendly.

Interface

yf.download(tickers, ...) -> pd.DataFrame

Parameters

Parameter	Description	Default	Valid values
tickers : str, list	List of tickers to download		E.g. "SPY AAPL MSFT", ["SPY", "AAPL", "MSFT"]
period: str	Either set period parameter or use start and end Don't mix with start & end	'max'	1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
interval: str	Intraday data cannot extend last 60 days * 1m - max 7 days within last 30 days * up to 90m - max 60 days * 60m, 1h - max 730 days (yes 1h is technically < 90m but this what Yahoo does)	'1d'	1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo
start: str	Download start date, inclusive	'1900-01-01' (if period=None)	'YYYY-MM-DD' string, _datetime, or epoch
end: str,dt,int	Download end date, exclusive	now (if period=None)	'YYYY-MM-DD' string, _datetime, or epoch
prepost: bool	Include Pre and Post market data in results?	False
auto_adjust: bool	Dividend-adjust all OHLC automatically?	False
back_adjust: bool	Deprecated	False
repair: bool	Detect problems in price data and repair: * very few prices = 0 or NaN * volume=0 despite price movement * very few prices 100x the rest	False
keepna: bool	Keep NaN rows returned by Yahoo?	False
rounding: bool	Optional. Round values using Yahoo-suggested precision?	False
group_by : str	Group by 'ticker' or 'column'	'column'
ignore_tz : bool	When aligning data from different exchanges, ignore different timezones?	True
threads : bool, int	How many threads to use for mass downloading. If True, number of threads = CPUs * 2	True
proxy: str	Optional. Proxy server URL scheme.	None
session: Session	Optional. Override default requests session	None
timeout: float,None	Optional. Stop waiting for response after N seconds.	10
progress : bool	Print progress bar.	True

Returns

Pandas DataFrame