Ticker#

class yfinance.Ticker(ticker, session=None)#

Initialize a Yahoo Finance Ticker object.

Parameters:
  • ticker (str | tuple[str, str]) – Yahoo Finance symbol (e.g. “AAPL”) or a tuple of (symbol, MIC) e.g. (‘OR’,’XPAR’) (MIC = market identifier code)

  • session (requests.Session, optional) – Custom requests session.

Attributes

actions
analyst_price_targets
balance_sheet
balancesheet
calendar

Returns a dictionary of events, earnings, and dividends for the ticker

capital_gains
cash_flow
cashflow
dividends
earnings
earnings_dates
earnings_estimate
earnings_history
eps_revisions
eps_trend
fast_info
financials
funds_data
growth_estimates
history_metadata
income_stmt
incomestmt
info
insider_purchases
insider_roster_holders
insider_transactions
institutional_holders
isin
major_holders
mutualfund_holders
news
options
quarterly_balance_sheet
quarterly_balancesheet
quarterly_cash_flow
quarterly_cashflow
quarterly_earnings
quarterly_financials
quarterly_income_stmt
quarterly_incomestmt
recommendations
recommendations_summary
revenue_estimate
sec_filings
shares
splits
sustainability
ttm_cash_flow
ttm_cashflow
ttm_financials
ttm_income_stmt
ttm_incomestmt
upgrades_downgrades
valuation

Methods

__init__(ticker, session=None)

Initialize a Yahoo Finance Ticker object.

Parameters:
  • ticker (str | tuple[str, str]) – Yahoo Finance symbol (e.g. “AAPL”) or a tuple of (symbol, MIC) e.g. (‘OR’,’XPAR’) (MIC = market identifier code)

  • session (requests.Session, optional) – Custom requests session.

get_actions(period='max') Series
get_analyst_price_targets() dict

Keys: current low high mean median

get_balance_sheet(as_dict=False, pretty=False, freq='yearly')
Parameters:
as_dict: bool

Return table as Python dict Default is False

pretty: bool

Format row names nicely for readability Default is False

freq: str

“yearly” or “quarterly” Default is “yearly”

get_balancesheet(as_dict=False, pretty=False, freq='yearly')
get_calendar() dict
get_capital_gains(period='max') Series
get_cash_flow(as_dict=False, pretty=False, freq='yearly') DataFrame | dict
Parameters:
as_dict: bool

Return table as Python dict Default is False

pretty: bool

Format row names nicely for readability Default is False

freq: str

“yearly” or “quarterly” Default is “yearly”

get_cashflow(as_dict=False, pretty=False, freq='yearly')
get_dividends(period='max') Series
get_earnings(as_dict=False, freq='yearly')
Parameters:
as_dict: bool

Return table as Python dict Default is False

freq: str

“yearly” or “quarterly” or “trailing” Default is “yearly”

get_earnings_dates(limit=12, offset=0) DataFrame | None
get_earnings_estimate(as_dict=False)

Index: 0q +1q 0y +1y Columns: numberOfAnalysts avg low high yearAgoEps growth

get_earnings_history(as_dict=False)

Index: pd.DatetimeIndex Columns: epsEstimate epsActual epsDifference surprisePercent

get_eps_revisions(as_dict=False)

Index: 0q +1q 0y +1y Columns: upLast7days upLast30days downLast7days downLast30days

get_eps_trend(as_dict=False)

Index: 0q +1q 0y +1y Columns: current 7daysAgo 30daysAgo 60daysAgo 90daysAgo

get_fast_info()
get_financials(as_dict=False, pretty=False, freq='yearly')
get_funds_data() FundsData | None
get_growth_estimates(as_dict=False)

Index: 0q +1q 0y +1y +5y -5y Columns: stock industry sector index

get_history_metadata(repair=<object object>) dict

repair default value depends on whether user requested price repair with previous history() call. If user did not set repair here, then it is set to match previous history() call.

get_income_stmt(as_dict=False, pretty=False, freq='yearly')
Parameters:
as_dict: bool

Return table as Python dict Default is False

pretty: bool

Format row names nicely for readability Default is False

freq: str

“yearly” or “quarterly” or “trailing” Default is “yearly”

get_incomestmt(as_dict=False, pretty=False, freq='yearly')
get_info() dict
get_insider_purchases(as_dict=False)
get_insider_roster_holders(as_dict=False)
get_insider_transactions(as_dict=False)
get_institutional_holders(as_dict=False)
get_isin() str | None
get_major_holders(as_dict=False)
get_mutualfund_holders(as_dict=False)
get_news(count=10, tab='news') list

Allowed options for tab: “news”, “all”, “press releases

get_recommendations(as_dict=False)

Returns a DataFrame with the recommendations Columns: period strongBuy buy hold sell strongSell

get_recommendations_summary(as_dict=False)
get_revenue_estimate(as_dict=False)

Index: 0q +1q 0y +1y Columns: numberOfAnalysts avg low high yearAgoRevenue growth

get_sec_filings() dict
get_shares(as_dict=False) DataFrame | dict
get_shares_full(start=None, end=None)
get_splits(period='max') Series
get_sustainability(as_dict=False)
get_upgrades_downgrades(as_dict=False)

Returns a DataFrame with the recommendations changes (upgrades/downgrades) Index: date of grade Columns: firm toGrade fromGrade action

get_valuation_measures()
history(*args, **kwargs) DataFrame
live(message_handler=None, verbose=True)
option_chain(date=None, tz=None)