yahoofinancials


Nameyahoofinancials JSON
Version 1.20 PyPI version JSON
download
home_pagehttps://github.com/JECSand/yahoofinancials
SummaryA powerful financial data module used for pulling both fundamental and technical data from Yahoo Finance
upload_time2023-12-17 08:03:42
maintainer
docs_urlNone
authorConnor Sanders
requires_python
licenseMIT
keywords finance data stocks commodities cryptocurrencies currencies forex yahoo finance
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            ===============
yahoofinancials
===============

A python module that returns stock, cryptocurrency, forex, mutual fund, commodity futures, ETF, and US Treasury financial data from Yahoo Finance.

.. image:: https://github.com/JECSand/yahoofinancials/actions/workflows/test.yml/badge.svg?branch=master
    :target: https://github.com/JECSand/yahoofinancials/actions/workflows/test.yml

.. image:: https://static.pepy.tech/badge/yahoofinancials
    :target: https://pepy.tech/project/yahoofinancials

.. image:: https://static.pepy.tech/badge/yahoofinancials/month
    :target: https://pepy.tech/project/yahoofinancials

.. image:: https://static.pepy.tech/badge/yahoofinancials/week
    :target: https://pepy.tech/project/yahoofinancials

Current Version: v1.20

Version Released: 12/17/2023

Report any bugs by opening an issue here: https://github.com/JECSand/yahoofinancials/issues

Overview
--------
A powerful financial data module used for pulling both fundamental and technical data from Yahoo Finance.

- New analytic methods in v1.20:
    - get_insights()
        - returns data for:
            - 'instrumentInfo'
            - 'companySnapshot'
            - 'recommendation'
            - 'sigDevs'
            - 'secReports'
    - get_recommendations()

- Example:

.. code-block:: python

    print(YahooFinancials('C').get_recommendations())

- Example Output:

.. code-block:: javascript

    {
        "C": [
            {
                "recommendedSymbols": [
                    {
                        "score": 0.239602,
                        "symbol": "BAC"
                    },
                    {
                    "score": 0.225134,
                    "symbol": "JPM"
                    },
                    {
                    "score": 0.167669,
                    "symbol": "WFC"
                    },
                    {
                    "score": 0.145864,
                    "symbol": "GS"
                    },
                    {
                    "score": 0.134071,
                    "symbol": "F"
                    }
                ],
                "symbol": "C"
            }
        ]
    }

- As of Version 1.20, YahooFinancials supports a new optional parameter called flat_format.
    - When `YahooFinancials(flat_format=True)`, financial statement data will return in a dict instead of a list. The keys of the dict will be the reporting dates.
    - Default is False, to ensure backwards compatibility.


- As of Version 1.9, YahooFinancials supports optional parameters for asynchronous execution, proxies, and international requests.

.. code-block:: python

    from yahoofinancials import YahooFinancials
    tickers = ['AAPL', 'GOOG', 'C']
    yahoo_financials = YahooFinancials(tickers, concurrent=True, max_workers=8, country="US")
    balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')
    print(balance_sheet_data_qt)

    proxy_addresses = [ "mysuperproxy.com:5000", "mysuperproxy.com:5001"]
    yahoo_financials = YahooFinancials(tickers, concurrent=True, proxies=proxy_addresses)
    balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')
    print(balance_sheet_data_qt)

Installation
-------------
- yahoofinancials runs on Python 3.7, 3.8, 3.9, 3.10, 3.11, and 3.12

1. Installation using pip:

- Linux/Mac:

.. code-block:: bash

    $ pip install yahoofinancials

- Windows (If python doesn't work for you in cmd, try running the following command with just py):

.. code-block::

    > python -m pip install yahoofinancials

2. Installation using github (Mac/Linux):

.. code-block:: bash

    $ git clone https://github.com/JECSand/yahoofinancials.git
    $ cd yahoofinancials
    $ python setup.py install

3. Demo using the included demo script:

.. code-block:: bash

    $ cd yahoofinancials
    $ python demo.py -h
    $ python demo.py
    $ python demo.py WFC C BAC

4. Test using the included unit testing script:

.. code-block:: bash

    $ cd yahoofinancials
    $ python test/test_yahoofinancials.py

Module Methods
--------------
- The financial data from all methods is returned as JSON.
- You can run multiple symbols at once using an inputted array or run an individual symbol using an inputted string.
- YahooFinancials works with Python 3.7, 3.8, 3.9, 3.10, 3.11 and 3.12 and runs on all operating systems. (Windows, Mac, Linux).

Featured Methods
^^^^^^^^^^^^^^^^
1. get_financial_stmts(frequency, statement_type, reformat=True)

   - frequency can be either 'annual' or 'quarterly'.
   - statement_type can be 'income', 'balance', 'cash' or a list of several.
   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
2. get_stock_price_data(reformat=True)

3. get_stock_earnings_data()

   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
4. get_summary_data(reformat=True)

   - Returns financial summary data for cryptocurrencies, stocks, currencies, ETFs, mutual funds, U.S. Treasuries, commodity futures, and indexes.
   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
5. get_stock_quote_type_data()

6. get_historical_price_data(start_date, end_date, time_interval)

   - This method will pull historical pricing data for stocks, currencies, ETFs, mutual funds, U.S. Treasuries, cryptocurrencies, commodities, and indexes.
   - start_date should be entered in the 'YYYY-MM-DD' format and is the first day that data will be pulled for.
   - end_date should be entered in the 'YYYY-MM-DD' format and is the last day that data will be pulled for.
   - time_interval can be either 'daily', 'weekly', or 'monthly'. This variable determines the time period interval for your pull.
   - Data response includes relevant pricing event data such as dividends and stock splits.
7. get_num_shares_outstanding(price_type='current')

   - price_type can also be set to 'average' to calculate the shares outstanding with the daily average price.

Additional Module Methods
^^^^^^^^^^^^^^^^^^^^^^^^^
- get_daily_dividend_data(start_date, end_date)
- get_stock_profile_data()
- get_financial_data()
- get_interest_expense()
- get_operating_income()
- get_total_operating_expense()
- get_total_revenue()
- get_cost_of_revenue()
- get_income_before_tax()
- get_income_tax_expense()
- get_esg_score_data()
- get_gross_profit()
- get_net_income_from_continuing_ops()
- get_research_and_development()
- get_current_price()
- get_current_change()
- get_current_percent_change()
- get_current_volume()
- get_prev_close_price()
- get_open_price()
- get_ten_day_avg_daily_volume()
- get_stock_exchange()
- get_market_cap()
- get_daily_low()
- get_daily_high()
- get_currency()
- get_yearly_high()
- get_yearly_low()
- get_dividend_yield()
- get_annual_avg_div_yield()
- get_five_yr_avg_div_yield()
- get_dividend_rate()
- get_annual_avg_div_rate()
- get_50day_moving_avg()
- get_200day_moving_avg()
- get_beta()
- get_payout_ratio()
- get_pe_ratio()
- get_price_to_sales()
- get_exdividend_date()
- get_book_value()
- get_ebit()
- get_net_income()
- get_earnings_per_share()
- get_key_statistics_data()
- get_stock_profile_data()
- get_financial_data()

Usage Examples
--------------
- The class constructor can take either a single ticker or a list of tickers as it's parameter.
- This makes it easy to initiate multiple classes for different groupings of financial assets.
- Quarterly statement data returns the last 4 periods of data, while annual returns the last 3.

Single Ticker Example
^^^^^^^^^^^^^^^^^^^^^

.. code-block:: python

    from yahoofinancials import YahooFinancials

    ticker = 'AAPL'
    yahoo_financials = YahooFinancials(ticker)

    balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')
    income_statement_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'income')
    all_statement_data_qt =  yahoo_financials.get_financial_stmts('quarterly', ['income', 'cash', 'balance'])
    apple_earnings_data = yahoo_financials.get_stock_earnings_data()
    apple_net_income = yahoo_financials.get_net_income()
    historical_stock_prices = yahoo_financials.get_historical_price_data('2008-09-15', '2018-09-15', 'weekly')

Lists of Tickers Example
^^^^^^^^^^^^^^^^^^^^^^^^

.. code-block:: python

    from yahoofinancials import YahooFinancials

    tech_stocks = ['AAPL', 'MSFT', 'INTC']
    bank_stocks = ['WFC', 'BAC', 'C']
    commodity_futures = ['GC=F', 'SI=F', 'CL=F']
    cryptocurrencies = ['BTC-USD', 'ETH-USD', 'XRP-USD']
    currencies = ['EURUSD=X', 'JPY=X', 'GBPUSD=X']
    mutual_funds = ['PRLAX', 'QASGX', 'HISFX']
    us_treasuries = ['^TNX', '^IRX', '^TYX']

    yahoo_financials_tech = YahooFinancials(tech_stocks)
    yahoo_financials_banks = YahooFinancials(bank_stocks)
    yahoo_financials_commodities = YahooFinancials(commodity_futures)
    yahoo_financials_cryptocurrencies = YahooFinancials(cryptocurrencies)
    yahoo_financials_currencies = YahooFinancials(currencies)
    yahoo_financials_mutualfunds = YahooFinancials(mutual_funds)
    yahoo_financials_treasuries = YahooFinancials(us_treasuries)

    tech_cash_flow_data_an = yahoo_financials_tech.get_financial_stmts('annual', 'cash')
    bank_cash_flow_data_an = yahoo_financials_banks.get_financial_stmts('annual', 'cash')

    banks_net_ebit = yahoo_financials_banks.get_ebit()
    tech_stock_price_data = yahoo_financials_tech.get_stock_price_data()
    daily_bank_stock_prices = yahoo_financials_banks.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
    daily_commodity_prices = yahoo_financials_commodities.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
    daily_crypto_prices = yahoo_financials_cryptocurrencies.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
    daily_currency_prices = yahoo_financials_currencies.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
    daily_mutualfund_prices = yahoo_financials_mutualfunds.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')
    daily_treasury_prices = yahoo_financials_treasuries.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')

Examples of Returned JSON Data
------------------------------

1. Annual Income Statement Data for Apple:


.. code-block:: python

    yahoo_financials = YahooFinancials('AAPL')
    print(yahoo_financials.get_financial_stmts('annual', 'income'))


.. code-block:: javascript

    {
        "incomeStatementHistory": {
            "AAPL": [
                {
                    "2016-09-24": {
                        "minorityInterest": null,
                        "otherOperatingExpenses": null,
                        "netIncomeFromContinuingOps": 45687000000,
                        "totalRevenue": 215639000000,
                        "totalOtherIncomeExpenseNet": 1348000000,
                        "discontinuedOperations": null,
                        "incomeTaxExpense": 15685000000,
                        "extraordinaryItems": null,
                        "grossProfit": 84263000000,
                        "netIncome": 45687000000,
                        "sellingGeneralAdministrative": 14194000000,
                        "interestExpense": null,
                        "costOfRevenue": 131376000000,
                        "researchDevelopment": 10045000000,
                        "netIncomeApplicableToCommonShares": 45687000000,
                        "effectOfAccountingCharges": null,
                        "incomeBeforeTax": 61372000000,
                        "otherItems": null,
                        "operatingIncome": 60024000000,
                        "ebit": 61372000000,
                        "nonRecurring": null,
                        "totalOperatingExpenses": 0
                    }
                }
            ]
        }
    }

2. Annual Balance Sheet Data for Apple:


.. code-block:: python

    yahoo_financials = YahooFinancials('AAPL')
    print(yahoo_financials.get_financial_stmts('annual', 'balance'))


.. code-block:: javascript

    {
        "balanceSheetHistory": {
            "AAPL": [
                {
                    "2016-09-24": {
                        "otherCurrentLiab": 8080000000,
                        "otherCurrentAssets": 8283000000,
                        "goodWill": 5414000000,
                        "shortTermInvestments": 46671000000,
                        "longTermInvestments": 170430000000,
                        "cash": 20484000000,
                        "netTangibleAssets": 119629000000,
                        "totalAssets": 321686000000,
                        "otherLiab": 36074000000,
                        "totalStockholderEquity": 128249000000,
                        "inventory": 2132000000,
                        "retainedEarnings": 96364000000,
                        "intangibleAssets": 3206000000,
                        "totalCurrentAssets": 106869000000,
                        "otherStockholderEquity": 634000000,
                        "shortLongTermDebt": 11605000000,
                        "propertyPlantEquipment": 27010000000,
                        "deferredLongTermLiab": 2930000000,
                        "netReceivables": 29299000000,
                        "otherAssets": 8757000000,
                        "longTermDebt": 75427000000,
                        "totalLiab": 193437000000,
                        "commonStock": 31251000000,
                        "accountsPayable": 59321000000,
                        "totalCurrentLiabilities": 79006000000
                    }
                }
            ]
        }
    }

3. Quarterly Cash Flow Statement Data for Citigroup:


.. code-block:: python

    yahoo_financials = YahooFinancials('C')
    print(yahoo_financials.get_financial_stmts('quarterly', 'cash'))


.. code-block:: javascript

    {
        "cashflowStatementHistoryQuarterly": {
            "C": [
                {
                    "2017-06-30": {
                        "totalCashFromOperatingActivities": -18505000000,
                        "effectOfExchangeRate": -117000000,
                        "totalCashFromFinancingActivities": 39798000000,
                        "netIncome": 3872000000,
                        "dividendsPaid": -760000000,
                        "salePurchaseOfStock": -1781000000,
                        "capitalExpenditures": -861000000,
                        "changeToLiabilities": -7626000000,
                        "otherCashflowsFromInvestingActivities": 82000000,
                        "totalCashflowsFromInvestingActivities": -22508000000,
                        "netBorrowings": 33586000000,
                        "depreciation": 901000000,
                        "changeInCash": -1332000000,
                        "changeToNetincome": 1444000000,
                        "otherCashflowsFromFinancingActivities": 8753000000,
                        "changeToOperatingActivities": -17096000000,
                        "investments": -23224000000
                    }
                }
            ]
        }
    }

4. Monthly Historical Stock Price Data for Wells Fargo:


.. code-block:: python

    yahoo_financials = YahooFinancials('WFC')
    print(yahoo_financials.get_historical_price_data("2018-07-10", "2018-08-10", "monthly"))


.. code-block:: javascript

    {
        "WFC": {
            "currency": "USD",
            "eventsData": {
                "dividends": {
                    "2018-08-01": {
                        "amount": 0.43,
                        "date": 1533821400,
                        "formatted_date": "2018-08-09"
                    }
                }
            },
            "firstTradeDate": {
                "date": 76233600,
                "formatted_date": "1972-06-01"
            },
            "instrumentType": "EQUITY",
            "prices": [
                {
                    "adjclose": 57.19147872924805,
                    "close": 57.61000061035156,
                    "date": 1533096000,
                    "formatted_date": "2018-08-01",
                    "high": 59.5,
                    "low": 57.08000183105469,
                    "open": 57.959999084472656,
                    "volume": 138922900
                }
            ],
            "timeZone": {
                "gmtOffset": -14400
            }
        }
    }

5. Monthly Historical Price Data for EURUSD:


.. code-block:: python

    yahoo_financials = YahooFinancials('EURUSD=X')
    print(yahoo_financials.get_historical_price_data("2018-07-10", "2018-08-10", "monthly"))


.. code-block:: javascript

    {
        "EURUSD=X": {
            "currency": "USD",
            "eventsData": {},
            "firstTradeDate": {
                "date": 1070236800,
                "formatted_date": "2003-12-01"
            },
            "instrumentType": "CURRENCY",
            "prices": [
                {
                    "adjclose": 1.1394712924957275,
                    "close": 1.1394712924957275,
                    "date": 1533078000,
                    "formatted_date": "2018-07-31",
                    "high": 1.169864296913147,
                    "low": 1.1365960836410522,
                    "open": 1.168961763381958,
                    "volume": 0
                }
            ],
            "timeZone": {
                "gmtOffset": 3600
            }
        }
    }

6. Monthly Historical Price Data for BTC-USD:


.. code-block:: python

    yahoo_financials = YahooFinancials('BTC-USD')
    print(yahoo_financials.get_historical_price_data("2018-07-10", "2018-08-10", "monthly"))


.. code-block:: javascript

    {
        "BTC-USD": {
            "currency": "USD",
            "eventsData": {},
            "firstTradeDate": {
                "date": 1279321200,
                "formatted_date": "2010-07-16"
            },
            "instrumentType": "CRYPTOCURRENCY",
            "prices": [
                {
                    "adjclose": 6285.02001953125,
                    "close": 6285.02001953125,
                    "date": 1533078000,
                    "formatted_date": "2018-07-31",
                    "high": 7760.740234375,
                    "low": 6133.02978515625,
                    "open": 7736.25,
                    "volume": 4334347882
                }
            ],
            "timeZone": {
                "gmtOffset": 3600
            }
        }
    }

7. Weekly Historical Price Data for Crude Oil Futures:


.. code-block:: python

    yahoo_financials = YahooFinancials('CL=F')
    print(yahoo_financials.get_historical_price_data("2018-08-01", "2018-08-10", "weekly"))


.. code-block:: javascript

    {
        "CL=F": {
            "currency": "USD",
            "eventsData": {},
            "firstTradeDate": {
                "date": 1522555200,
                "formatted_date": "2018-04-01"
            },
            "instrumentType": "FUTURE",
            "prices": [
                {
                    "adjclose": 68.58999633789062,
                    "close": 68.58999633789062,
                    "date": 1532923200,
                    "formatted_date": "2018-07-30",
                    "high": 69.3499984741211,
                    "low": 66.91999816894531,
                    "open": 68.37000274658203,
                    "volume": 683048039
                },
                {
                    "adjclose": 67.75,
                    "close": 67.75,
                    "date": 1533528000,
                    "formatted_date": "2018-08-06",
                    "high": 69.91999816894531,
                    "low": 66.13999938964844,
                    "open": 68.76000213623047,
                    "volume": 1102357981
                }
            ],
            "timeZone": {
                "gmtOffset": -14400
            }
        }
    }

8. Apple Stock Quote Data:


.. code-block:: python

    yahoo_financials = YahooFinancials('AAPL')
    print(yahoo_financials.get_stock_quote_type_data())


.. code-block:: javascript

    {
        "AAPL": {
            "underlyingExchangeSymbol": null,
            "exchangeTimezoneName": "America/New_York",
            "underlyingSymbol": null,
            "headSymbol": null,
            "shortName": "Apple Inc.",
            "symbol": "AAPL",
            "uuid": "8b10e4ae-9eeb-3684-921a-9ab27e4d87aa",
            "gmtOffSetMilliseconds": "-14400000",
            "exchange": "NMS",
            "exchangeTimezoneShortName": "EDT",
            "messageBoardId": "finmb_24937",
            "longName": "Apple Inc.",
            "market": "us_market",
            "quoteType": "EQUITY"
        }
    }

9. U.S. Treasury Current Pricing Data:


.. code-block:: python

    yahoo_financials = YahooFinancials(['^TNX', '^IRX', '^TYX'])
    print(yahoo_financials.get_current_price())


.. code-block:: javascript

    {
        "^IRX": 2.033,
        "^TNX": 2.895,
        "^TYX": 3.062
    }

10. BTC-USD Summary Data:


.. code-block:: python

    yahoo_financials = YahooFinancials('BTC-USD')
    print(yahoo_financials.get_summary_data())


.. code-block:: javascript

    {
        "BTC-USD": {
            "algorithm": "SHA256",
            "ask": null,
            "askSize": null,
            "averageDailyVolume10Day": 545573809,
            "averageVolume": 496761640,
            "averageVolume10days": 545573809,
            "beta": null,
            "bid": null,
            "bidSize": null,
            "circulatingSupply": 17209812,
            "currency": "USD",
            "dayHigh": 6266.5,
            "dayLow": 5891.87,
            "dividendRate": null,
            "dividendYield": null,
            "exDividendDate": "-",
            "expireDate": "-",
            "fiftyDayAverage": 6989.074,
            "fiftyTwoWeekHigh": 19870.62,
            "fiftyTwoWeekLow": 2979.88,
            "fiveYearAvgDividendYield": null,
            "forwardPE": null,
            "fromCurrency": "BTC",
            "lastMarket": "CCCAGG",
            "marketCap": 106325663744,
            "maxAge": 1,
            "maxSupply": 21000000,
            "navPrice": null,
            "open": 6263.2,
            "openInterest": null,
            "payoutRatio": null,
            "previousClose": 6263.2,
            "priceHint": 2,
            "priceToSalesTrailing12Months": null,
            "regularMarketDayHigh": 6266.5,
            "regularMarketDayLow": 5891.87,
            "regularMarketOpen": 6263.2,
            "regularMarketPreviousClose": 6263.2,
            "regularMarketVolume": 755834368,
            "startDate": "2009-01-03",
            "strikePrice": null,
            "totalAssets": null,
            "tradeable": false,
            "trailingAnnualDividendRate": null,
            "trailingAnnualDividendYield": null,
            "twoHundredDayAverage": 8165.154,
            "volume": 755834368,
            "volume24Hr": 750196480,
            "volumeAllCurrencies": 2673437184,
            "yield": null,
            "ytdReturn": null
        }
    }

11. Apple Key Statistics Data:


.. code-block:: python

    yahoo_financials = YahooFinancials('AAPL')
    print(yahoo_financials.get_key_statistics_data())


.. code-block:: javascript

    {
        "AAPL": {
            "annualHoldingsTurnover": null,
            "enterpriseToRevenue": 2.973,
            "beta3Year": null,
            "profitMargins": 0.22413999,
            "enterpriseToEbitda": 9.652,
            "52WeekChange": -0.12707871,
            "morningStarRiskRating": null,
            "forwardEps": 13.49,
            "revenueQuarterlyGrowth": null,
            "sharesOutstanding": 4729800192,
            "fundInceptionDate": "-",
            "annualReportExpenseRatio": null,
            "totalAssets": null,
            "bookValue": 22.534,
            "sharesShort": 44915125,
            "sharesPercentSharesOut": 0.0095,
            "fundFamily": null,
            "lastFiscalYearEnd": 1538179200,
            "heldPercentInstitutions": 0.61208,
            "netIncomeToCommon": 59531001856,
            "trailingEps": 11.91,
            "lastDividendValue": null,
            "SandP52WeekChange": -0.06475246,
            "priceToBook": 6.7582316,
            "heldPercentInsiders": 0.00072999997,
            "nextFiscalYearEnd": 1601337600,
            "yield": null,
            "mostRecentQuarter": 1538179200,
            "shortRatio": 1,
            "sharesShortPreviousMonthDate": "2018-10-31",
            "floatShares": 4489763410,
            "beta": 1.127094,
            "enterpriseValue": 789555511296,
            "priceHint": 2,
            "threeYearAverageReturn": null,
            "lastSplitDate": "2014-06-09",
            "lastSplitFactor": "1/7",
            "legalType": null,
            "morningStarOverallRating": null,
            "earningsQuarterlyGrowth": 0.318,
            "priceToSalesTrailing12Months": null,
            "dateShortInterest": 1543536000,
            "pegRatio": 0.98,
            "ytdReturn": null,
            "forwardPE": 11.289103,
            "maxAge": 1,
            "lastCapGain": null,
            "shortPercentOfFloat": 0.0088,
            "sharesShortPriorMonth": 36469092,
            "category": null,
            "fiveYearAverageReturn": null
        }
    }

12. Apple and Wells Fargo Daily Dividend Data:


.. code-block:: python

    start_date = '1987-09-15'
    end_date = '1988-09-15'
    yahoo_financials = YahooFinancials(['AAPL', 'WFC'])
    print(yahoo_financials.get_daily_dividend_data(start_date, end_date))


.. code-block:: javascript

    {
        "AAPL": [
            {
                "date": 564157800,
                "formatted_date": "1987-11-17",
                "amount": 0.08
            },
            {
                "date": 571674600,
                "formatted_date": "1988-02-12",
                "amount": 0.08
            },
            {
                "date": 579792600,
                "formatted_date": "1988-05-16",
                "amount": 0.08
            },
            {
                "date": 587655000,
                "formatted_date": "1988-08-15",
                "amount": 0.08
            }
        ],
        "WFC": [
            {
                "date": 562861800,
                "formatted_date": "1987-11-02",
                "amount": 0.3008
            },
            {
                "date": 570724200,
                "formatted_date": "1988-02-01",
                "amount": 0.3008
            },
            {
                "date": 578583000,
                "formatted_date": "1988-05-02",
                "amount": 0.3344
            },
            {
                "date": 586445400,
                "formatted_date": "1988-08-01",
                "amount": 0.3344
            }
        ]
    }

13. Apple key Financial Data:


.. code-block:: python

    yahoo_financials = YahooFinancials("AAPL")
    print(yahoo_financials.get_financial_data())


.. code-block:: javascript

    {
        'AAPL': {
            'ebitdaMargins': 0.29395,
            'profitMargins': 0.21238,
            'grossMargins': 0.37818,
            'operatingCashflow': 69390999552,
            'revenueGrowth': 0.018,
            'operatingMargins': 0.24572,
            'ebitda': 76476997632,
            'targetLowPrice': 150,
            'recommendationKey': 'buy',
            'grossProfits': 98392000000,
            'freeCashflow': 42914250752,
            'targetMedianPrice': 270,
            'currentPrice': 261.78,
            'earningsGrowth': 0.039,
            'currentRatio': 1.54,
            'returnOnAssets': 0.11347,
            'numberOfAnalystOpinions': 40,
            'targetMeanPrice': 255.51,
            'debtToEquity': 119.405,
            'returnOnEquity': 0.55917,
            'targetHighPrice': 300,
            'totalCash': 100556996608,
            'totalDebt': 108046999552,
            'totalRevenue': 260174004224,
            'totalCashPerShare': 22.631,
            'financialCurrency': 'USD',
            'maxAge': 86400,
            'revenuePerShare': 56.341,
            'quickRatio': 1.384,
            'recommendationMean': 2.2
        }
    }



            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/JECSand/yahoofinancials",
    "name": "yahoofinancials",
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "keywords": "finance data,stocks,commodities,cryptocurrencies,currencies,forex,yahoo finance",
    "author": "Connor Sanders",
    "author_email": "connor@exceleri.com",
    "download_url": "https://files.pythonhosted.org/packages/02/0c/20f6018aeb08903b4efc6f8aff1bc988c4da1be28adda21fb84bb863f58b/yahoofinancials-1.20.tar.gz",
    "platform": null,
    "description": "===============\nyahoofinancials\n===============\n\nA python module that returns stock, cryptocurrency, forex, mutual fund, commodity futures, ETF, and US Treasury financial data from Yahoo Finance.\n\n.. image:: https://github.com/JECSand/yahoofinancials/actions/workflows/test.yml/badge.svg?branch=master\n    :target: https://github.com/JECSand/yahoofinancials/actions/workflows/test.yml\n\n.. image:: https://static.pepy.tech/badge/yahoofinancials\n    :target: https://pepy.tech/project/yahoofinancials\n\n.. image:: https://static.pepy.tech/badge/yahoofinancials/month\n    :target: https://pepy.tech/project/yahoofinancials\n\n.. image:: https://static.pepy.tech/badge/yahoofinancials/week\n    :target: https://pepy.tech/project/yahoofinancials\n\nCurrent Version: v1.20\n\nVersion Released: 12/17/2023\n\nReport any bugs by opening an issue here: https://github.com/JECSand/yahoofinancials/issues\n\nOverview\n--------\nA powerful financial data module used for pulling both fundamental and technical data from Yahoo Finance.\n\n- New analytic methods in v1.20:\n    - get_insights()\n        - returns data for:\n            - 'instrumentInfo'\n            - 'companySnapshot'\n            - 'recommendation'\n            - 'sigDevs'\n            - 'secReports'\n    - get_recommendations()\n\n- Example:\n\n.. code-block:: python\n\n    print(YahooFinancials('C').get_recommendations())\n\n- Example Output:\n\n.. code-block:: javascript\n\n    {\n        \"C\": [\n            {\n                \"recommendedSymbols\": [\n                    {\n                        \"score\": 0.239602,\n                        \"symbol\": \"BAC\"\n                    },\n                    {\n                    \"score\": 0.225134,\n                    \"symbol\": \"JPM\"\n                    },\n                    {\n                    \"score\": 0.167669,\n                    \"symbol\": \"WFC\"\n                    },\n                    {\n                    \"score\": 0.145864,\n                    \"symbol\": \"GS\"\n                    },\n                    {\n                    \"score\": 0.134071,\n                    \"symbol\": \"F\"\n                    }\n                ],\n                \"symbol\": \"C\"\n            }\n        ]\n    }\n\n- As of Version 1.20, YahooFinancials supports a new optional parameter called flat_format.\n    - When `YahooFinancials(flat_format=True)`, financial statement data will return in a dict instead of a list. The keys of the dict will be the reporting dates.\n    - Default is False, to ensure backwards compatibility.\n\n\n- As of Version 1.9, YahooFinancials supports optional parameters for asynchronous execution, proxies, and international requests.\n\n.. code-block:: python\n\n    from yahoofinancials import YahooFinancials\n    tickers = ['AAPL', 'GOOG', 'C']\n    yahoo_financials = YahooFinancials(tickers, concurrent=True, max_workers=8, country=\"US\")\n    balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')\n    print(balance_sheet_data_qt)\n\n    proxy_addresses = [ \"mysuperproxy.com:5000\", \"mysuperproxy.com:5001\"]\n    yahoo_financials = YahooFinancials(tickers, concurrent=True, proxies=proxy_addresses)\n    balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')\n    print(balance_sheet_data_qt)\n\nInstallation\n-------------\n- yahoofinancials runs on Python 3.7, 3.8, 3.9, 3.10, 3.11, and 3.12\n\n1. Installation using pip:\n\n- Linux/Mac:\n\n.. code-block:: bash\n\n    $ pip install yahoofinancials\n\n- Windows (If python doesn't work for you in cmd, try running the following command with just py):\n\n.. code-block::\n\n    > python -m pip install yahoofinancials\n\n2. Installation using github (Mac/Linux):\n\n.. code-block:: bash\n\n    $ git clone https://github.com/JECSand/yahoofinancials.git\n    $ cd yahoofinancials\n    $ python setup.py install\n\n3. Demo using the included demo script:\n\n.. code-block:: bash\n\n    $ cd yahoofinancials\n    $ python demo.py -h\n    $ python demo.py\n    $ python demo.py WFC C BAC\n\n4. Test using the included unit testing script:\n\n.. code-block:: bash\n\n    $ cd yahoofinancials\n    $ python test/test_yahoofinancials.py\n\nModule Methods\n--------------\n- The financial data from all methods is returned as JSON.\n- You can run multiple symbols at once using an inputted array or run an individual symbol using an inputted string.\n- YahooFinancials works with Python 3.7, 3.8, 3.9, 3.10, 3.11 and 3.12 and runs on all operating systems. (Windows, Mac, Linux).\n\nFeatured Methods\n^^^^^^^^^^^^^^^^\n1. get_financial_stmts(frequency, statement_type, reformat=True)\n\n   - frequency can be either 'annual' or 'quarterly'.\n   - statement_type can be 'income', 'balance', 'cash' or a list of several.\n   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.\n2. get_stock_price_data(reformat=True)\n\n3. get_stock_earnings_data()\n\n   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.\n4. get_summary_data(reformat=True)\n\n   - Returns financial summary data for cryptocurrencies, stocks, currencies, ETFs, mutual funds, U.S. Treasuries, commodity futures, and indexes.\n   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.\n5. get_stock_quote_type_data()\n\n6. get_historical_price_data(start_date, end_date, time_interval)\n\n   - This method will pull historical pricing data for stocks, currencies, ETFs, mutual funds, U.S. Treasuries, cryptocurrencies, commodities, and indexes.\n   - start_date should be entered in the 'YYYY-MM-DD' format and is the first day that data will be pulled for.\n   - end_date should be entered in the 'YYYY-MM-DD' format and is the last day that data will be pulled for.\n   - time_interval can be either 'daily', 'weekly', or 'monthly'. This variable determines the time period interval for your pull.\n   - Data response includes relevant pricing event data such as dividends and stock splits.\n7. get_num_shares_outstanding(price_type='current')\n\n   - price_type can also be set to 'average' to calculate the shares outstanding with the daily average price.\n\nAdditional Module Methods\n^^^^^^^^^^^^^^^^^^^^^^^^^\n- get_daily_dividend_data(start_date, end_date)\n- get_stock_profile_data()\n- get_financial_data()\n- get_interest_expense()\n- get_operating_income()\n- get_total_operating_expense()\n- get_total_revenue()\n- get_cost_of_revenue()\n- get_income_before_tax()\n- get_income_tax_expense()\n- get_esg_score_data()\n- get_gross_profit()\n- get_net_income_from_continuing_ops()\n- get_research_and_development()\n- get_current_price()\n- get_current_change()\n- get_current_percent_change()\n- get_current_volume()\n- get_prev_close_price()\n- get_open_price()\n- get_ten_day_avg_daily_volume()\n- get_stock_exchange()\n- get_market_cap()\n- get_daily_low()\n- get_daily_high()\n- get_currency()\n- get_yearly_high()\n- get_yearly_low()\n- get_dividend_yield()\n- get_annual_avg_div_yield()\n- get_five_yr_avg_div_yield()\n- get_dividend_rate()\n- get_annual_avg_div_rate()\n- get_50day_moving_avg()\n- get_200day_moving_avg()\n- get_beta()\n- get_payout_ratio()\n- get_pe_ratio()\n- get_price_to_sales()\n- get_exdividend_date()\n- get_book_value()\n- get_ebit()\n- get_net_income()\n- get_earnings_per_share()\n- get_key_statistics_data()\n- get_stock_profile_data()\n- get_financial_data()\n\nUsage Examples\n--------------\n- The class constructor can take either a single ticker or a list of tickers as it's parameter.\n- This makes it easy to initiate multiple classes for different groupings of financial assets.\n- Quarterly statement data returns the last 4 periods of data, while annual returns the last 3.\n\nSingle Ticker Example\n^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    from yahoofinancials import YahooFinancials\n\n    ticker = 'AAPL'\n    yahoo_financials = YahooFinancials(ticker)\n\n    balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')\n    income_statement_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'income')\n    all_statement_data_qt =  yahoo_financials.get_financial_stmts('quarterly', ['income', 'cash', 'balance'])\n    apple_earnings_data = yahoo_financials.get_stock_earnings_data()\n    apple_net_income = yahoo_financials.get_net_income()\n    historical_stock_prices = yahoo_financials.get_historical_price_data('2008-09-15', '2018-09-15', 'weekly')\n\nLists of Tickers Example\n^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    from yahoofinancials import YahooFinancials\n\n    tech_stocks = ['AAPL', 'MSFT', 'INTC']\n    bank_stocks = ['WFC', 'BAC', 'C']\n    commodity_futures = ['GC=F', 'SI=F', 'CL=F']\n    cryptocurrencies = ['BTC-USD', 'ETH-USD', 'XRP-USD']\n    currencies = ['EURUSD=X', 'JPY=X', 'GBPUSD=X']\n    mutual_funds = ['PRLAX', 'QASGX', 'HISFX']\n    us_treasuries = ['^TNX', '^IRX', '^TYX']\n\n    yahoo_financials_tech = YahooFinancials(tech_stocks)\n    yahoo_financials_banks = YahooFinancials(bank_stocks)\n    yahoo_financials_commodities = YahooFinancials(commodity_futures)\n    yahoo_financials_cryptocurrencies = YahooFinancials(cryptocurrencies)\n    yahoo_financials_currencies = YahooFinancials(currencies)\n    yahoo_financials_mutualfunds = YahooFinancials(mutual_funds)\n    yahoo_financials_treasuries = YahooFinancials(us_treasuries)\n\n    tech_cash_flow_data_an = yahoo_financials_tech.get_financial_stmts('annual', 'cash')\n    bank_cash_flow_data_an = yahoo_financials_banks.get_financial_stmts('annual', 'cash')\n\n    banks_net_ebit = yahoo_financials_banks.get_ebit()\n    tech_stock_price_data = yahoo_financials_tech.get_stock_price_data()\n    daily_bank_stock_prices = yahoo_financials_banks.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')\n    daily_commodity_prices = yahoo_financials_commodities.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')\n    daily_crypto_prices = yahoo_financials_cryptocurrencies.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')\n    daily_currency_prices = yahoo_financials_currencies.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')\n    daily_mutualfund_prices = yahoo_financials_mutualfunds.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')\n    daily_treasury_prices = yahoo_financials_treasuries.get_historical_price_data('2008-09-15', '2018-09-15', 'daily')\n\nExamples of Returned JSON Data\n------------------------------\n\n1. Annual Income Statement Data for Apple:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('AAPL')\n    print(yahoo_financials.get_financial_stmts('annual', 'income'))\n\n\n.. code-block:: javascript\n\n    {\n        \"incomeStatementHistory\": {\n            \"AAPL\": [\n                {\n                    \"2016-09-24\": {\n                        \"minorityInterest\": null,\n                        \"otherOperatingExpenses\": null,\n                        \"netIncomeFromContinuingOps\": 45687000000,\n                        \"totalRevenue\": 215639000000,\n                        \"totalOtherIncomeExpenseNet\": 1348000000,\n                        \"discontinuedOperations\": null,\n                        \"incomeTaxExpense\": 15685000000,\n                        \"extraordinaryItems\": null,\n                        \"grossProfit\": 84263000000,\n                        \"netIncome\": 45687000000,\n                        \"sellingGeneralAdministrative\": 14194000000,\n                        \"interestExpense\": null,\n                        \"costOfRevenue\": 131376000000,\n                        \"researchDevelopment\": 10045000000,\n                        \"netIncomeApplicableToCommonShares\": 45687000000,\n                        \"effectOfAccountingCharges\": null,\n                        \"incomeBeforeTax\": 61372000000,\n                        \"otherItems\": null,\n                        \"operatingIncome\": 60024000000,\n                        \"ebit\": 61372000000,\n                        \"nonRecurring\": null,\n                        \"totalOperatingExpenses\": 0\n                    }\n                }\n            ]\n        }\n    }\n\n2. Annual Balance Sheet Data for Apple:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('AAPL')\n    print(yahoo_financials.get_financial_stmts('annual', 'balance'))\n\n\n.. code-block:: javascript\n\n    {\n        \"balanceSheetHistory\": {\n            \"AAPL\": [\n                {\n                    \"2016-09-24\": {\n                        \"otherCurrentLiab\": 8080000000,\n                        \"otherCurrentAssets\": 8283000000,\n                        \"goodWill\": 5414000000,\n                        \"shortTermInvestments\": 46671000000,\n                        \"longTermInvestments\": 170430000000,\n                        \"cash\": 20484000000,\n                        \"netTangibleAssets\": 119629000000,\n                        \"totalAssets\": 321686000000,\n                        \"otherLiab\": 36074000000,\n                        \"totalStockholderEquity\": 128249000000,\n                        \"inventory\": 2132000000,\n                        \"retainedEarnings\": 96364000000,\n                        \"intangibleAssets\": 3206000000,\n                        \"totalCurrentAssets\": 106869000000,\n                        \"otherStockholderEquity\": 634000000,\n                        \"shortLongTermDebt\": 11605000000,\n                        \"propertyPlantEquipment\": 27010000000,\n                        \"deferredLongTermLiab\": 2930000000,\n                        \"netReceivables\": 29299000000,\n                        \"otherAssets\": 8757000000,\n                        \"longTermDebt\": 75427000000,\n                        \"totalLiab\": 193437000000,\n                        \"commonStock\": 31251000000,\n                        \"accountsPayable\": 59321000000,\n                        \"totalCurrentLiabilities\": 79006000000\n                    }\n                }\n            ]\n        }\n    }\n\n3. Quarterly Cash Flow Statement Data for Citigroup:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('C')\n    print(yahoo_financials.get_financial_stmts('quarterly', 'cash'))\n\n\n.. code-block:: javascript\n\n    {\n        \"cashflowStatementHistoryQuarterly\": {\n            \"C\": [\n                {\n                    \"2017-06-30\": {\n                        \"totalCashFromOperatingActivities\": -18505000000,\n                        \"effectOfExchangeRate\": -117000000,\n                        \"totalCashFromFinancingActivities\": 39798000000,\n                        \"netIncome\": 3872000000,\n                        \"dividendsPaid\": -760000000,\n                        \"salePurchaseOfStock\": -1781000000,\n                        \"capitalExpenditures\": -861000000,\n                        \"changeToLiabilities\": -7626000000,\n                        \"otherCashflowsFromInvestingActivities\": 82000000,\n                        \"totalCashflowsFromInvestingActivities\": -22508000000,\n                        \"netBorrowings\": 33586000000,\n                        \"depreciation\": 901000000,\n                        \"changeInCash\": -1332000000,\n                        \"changeToNetincome\": 1444000000,\n                        \"otherCashflowsFromFinancingActivities\": 8753000000,\n                        \"changeToOperatingActivities\": -17096000000,\n                        \"investments\": -23224000000\n                    }\n                }\n            ]\n        }\n    }\n\n4. Monthly Historical Stock Price Data for Wells Fargo:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('WFC')\n    print(yahoo_financials.get_historical_price_data(\"2018-07-10\", \"2018-08-10\", \"monthly\"))\n\n\n.. code-block:: javascript\n\n    {\n        \"WFC\": {\n            \"currency\": \"USD\",\n            \"eventsData\": {\n                \"dividends\": {\n                    \"2018-08-01\": {\n                        \"amount\": 0.43,\n                        \"date\": 1533821400,\n                        \"formatted_date\": \"2018-08-09\"\n                    }\n                }\n            },\n            \"firstTradeDate\": {\n                \"date\": 76233600,\n                \"formatted_date\": \"1972-06-01\"\n            },\n            \"instrumentType\": \"EQUITY\",\n            \"prices\": [\n                {\n                    \"adjclose\": 57.19147872924805,\n                    \"close\": 57.61000061035156,\n                    \"date\": 1533096000,\n                    \"formatted_date\": \"2018-08-01\",\n                    \"high\": 59.5,\n                    \"low\": 57.08000183105469,\n                    \"open\": 57.959999084472656,\n                    \"volume\": 138922900\n                }\n            ],\n            \"timeZone\": {\n                \"gmtOffset\": -14400\n            }\n        }\n    }\n\n5. Monthly Historical Price Data for EURUSD:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('EURUSD=X')\n    print(yahoo_financials.get_historical_price_data(\"2018-07-10\", \"2018-08-10\", \"monthly\"))\n\n\n.. code-block:: javascript\n\n    {\n        \"EURUSD=X\": {\n            \"currency\": \"USD\",\n            \"eventsData\": {},\n            \"firstTradeDate\": {\n                \"date\": 1070236800,\n                \"formatted_date\": \"2003-12-01\"\n            },\n            \"instrumentType\": \"CURRENCY\",\n            \"prices\": [\n                {\n                    \"adjclose\": 1.1394712924957275,\n                    \"close\": 1.1394712924957275,\n                    \"date\": 1533078000,\n                    \"formatted_date\": \"2018-07-31\",\n                    \"high\": 1.169864296913147,\n                    \"low\": 1.1365960836410522,\n                    \"open\": 1.168961763381958,\n                    \"volume\": 0\n                }\n            ],\n            \"timeZone\": {\n                \"gmtOffset\": 3600\n            }\n        }\n    }\n\n6. Monthly Historical Price Data for BTC-USD:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('BTC-USD')\n    print(yahoo_financials.get_historical_price_data(\"2018-07-10\", \"2018-08-10\", \"monthly\"))\n\n\n.. code-block:: javascript\n\n    {\n        \"BTC-USD\": {\n            \"currency\": \"USD\",\n            \"eventsData\": {},\n            \"firstTradeDate\": {\n                \"date\": 1279321200,\n                \"formatted_date\": \"2010-07-16\"\n            },\n            \"instrumentType\": \"CRYPTOCURRENCY\",\n            \"prices\": [\n                {\n                    \"adjclose\": 6285.02001953125,\n                    \"close\": 6285.02001953125,\n                    \"date\": 1533078000,\n                    \"formatted_date\": \"2018-07-31\",\n                    \"high\": 7760.740234375,\n                    \"low\": 6133.02978515625,\n                    \"open\": 7736.25,\n                    \"volume\": 4334347882\n                }\n            ],\n            \"timeZone\": {\n                \"gmtOffset\": 3600\n            }\n        }\n    }\n\n7. Weekly Historical Price Data for Crude Oil Futures:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('CL=F')\n    print(yahoo_financials.get_historical_price_data(\"2018-08-01\", \"2018-08-10\", \"weekly\"))\n\n\n.. code-block:: javascript\n\n    {\n        \"CL=F\": {\n            \"currency\": \"USD\",\n            \"eventsData\": {},\n            \"firstTradeDate\": {\n                \"date\": 1522555200,\n                \"formatted_date\": \"2018-04-01\"\n            },\n            \"instrumentType\": \"FUTURE\",\n            \"prices\": [\n                {\n                    \"adjclose\": 68.58999633789062,\n                    \"close\": 68.58999633789062,\n                    \"date\": 1532923200,\n                    \"formatted_date\": \"2018-07-30\",\n                    \"high\": 69.3499984741211,\n                    \"low\": 66.91999816894531,\n                    \"open\": 68.37000274658203,\n                    \"volume\": 683048039\n                },\n                {\n                    \"adjclose\": 67.75,\n                    \"close\": 67.75,\n                    \"date\": 1533528000,\n                    \"formatted_date\": \"2018-08-06\",\n                    \"high\": 69.91999816894531,\n                    \"low\": 66.13999938964844,\n                    \"open\": 68.76000213623047,\n                    \"volume\": 1102357981\n                }\n            ],\n            \"timeZone\": {\n                \"gmtOffset\": -14400\n            }\n        }\n    }\n\n8. Apple Stock Quote Data:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('AAPL')\n    print(yahoo_financials.get_stock_quote_type_data())\n\n\n.. code-block:: javascript\n\n    {\n        \"AAPL\": {\n            \"underlyingExchangeSymbol\": null,\n            \"exchangeTimezoneName\": \"America/New_York\",\n            \"underlyingSymbol\": null,\n            \"headSymbol\": null,\n            \"shortName\": \"Apple Inc.\",\n            \"symbol\": \"AAPL\",\n            \"uuid\": \"8b10e4ae-9eeb-3684-921a-9ab27e4d87aa\",\n            \"gmtOffSetMilliseconds\": \"-14400000\",\n            \"exchange\": \"NMS\",\n            \"exchangeTimezoneShortName\": \"EDT\",\n            \"messageBoardId\": \"finmb_24937\",\n            \"longName\": \"Apple Inc.\",\n            \"market\": \"us_market\",\n            \"quoteType\": \"EQUITY\"\n        }\n    }\n\n9. U.S. Treasury Current Pricing Data:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials(['^TNX', '^IRX', '^TYX'])\n    print(yahoo_financials.get_current_price())\n\n\n.. code-block:: javascript\n\n    {\n        \"^IRX\": 2.033,\n        \"^TNX\": 2.895,\n        \"^TYX\": 3.062\n    }\n\n10. BTC-USD Summary Data:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('BTC-USD')\n    print(yahoo_financials.get_summary_data())\n\n\n.. code-block:: javascript\n\n    {\n        \"BTC-USD\": {\n            \"algorithm\": \"SHA256\",\n            \"ask\": null,\n            \"askSize\": null,\n            \"averageDailyVolume10Day\": 545573809,\n            \"averageVolume\": 496761640,\n            \"averageVolume10days\": 545573809,\n            \"beta\": null,\n            \"bid\": null,\n            \"bidSize\": null,\n            \"circulatingSupply\": 17209812,\n            \"currency\": \"USD\",\n            \"dayHigh\": 6266.5,\n            \"dayLow\": 5891.87,\n            \"dividendRate\": null,\n            \"dividendYield\": null,\n            \"exDividendDate\": \"-\",\n            \"expireDate\": \"-\",\n            \"fiftyDayAverage\": 6989.074,\n            \"fiftyTwoWeekHigh\": 19870.62,\n            \"fiftyTwoWeekLow\": 2979.88,\n            \"fiveYearAvgDividendYield\": null,\n            \"forwardPE\": null,\n            \"fromCurrency\": \"BTC\",\n            \"lastMarket\": \"CCCAGG\",\n            \"marketCap\": 106325663744,\n            \"maxAge\": 1,\n            \"maxSupply\": 21000000,\n            \"navPrice\": null,\n            \"open\": 6263.2,\n            \"openInterest\": null,\n            \"payoutRatio\": null,\n            \"previousClose\": 6263.2,\n            \"priceHint\": 2,\n            \"priceToSalesTrailing12Months\": null,\n            \"regularMarketDayHigh\": 6266.5,\n            \"regularMarketDayLow\": 5891.87,\n            \"regularMarketOpen\": 6263.2,\n            \"regularMarketPreviousClose\": 6263.2,\n            \"regularMarketVolume\": 755834368,\n            \"startDate\": \"2009-01-03\",\n            \"strikePrice\": null,\n            \"totalAssets\": null,\n            \"tradeable\": false,\n            \"trailingAnnualDividendRate\": null,\n            \"trailingAnnualDividendYield\": null,\n            \"twoHundredDayAverage\": 8165.154,\n            \"volume\": 755834368,\n            \"volume24Hr\": 750196480,\n            \"volumeAllCurrencies\": 2673437184,\n            \"yield\": null,\n            \"ytdReturn\": null\n        }\n    }\n\n11. Apple Key Statistics Data:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials('AAPL')\n    print(yahoo_financials.get_key_statistics_data())\n\n\n.. code-block:: javascript\n\n    {\n        \"AAPL\": {\n            \"annualHoldingsTurnover\": null,\n            \"enterpriseToRevenue\": 2.973,\n            \"beta3Year\": null,\n            \"profitMargins\": 0.22413999,\n            \"enterpriseToEbitda\": 9.652,\n            \"52WeekChange\": -0.12707871,\n            \"morningStarRiskRating\": null,\n            \"forwardEps\": 13.49,\n            \"revenueQuarterlyGrowth\": null,\n            \"sharesOutstanding\": 4729800192,\n            \"fundInceptionDate\": \"-\",\n            \"annualReportExpenseRatio\": null,\n            \"totalAssets\": null,\n            \"bookValue\": 22.534,\n            \"sharesShort\": 44915125,\n            \"sharesPercentSharesOut\": 0.0095,\n            \"fundFamily\": null,\n            \"lastFiscalYearEnd\": 1538179200,\n            \"heldPercentInstitutions\": 0.61208,\n            \"netIncomeToCommon\": 59531001856,\n            \"trailingEps\": 11.91,\n            \"lastDividendValue\": null,\n            \"SandP52WeekChange\": -0.06475246,\n            \"priceToBook\": 6.7582316,\n            \"heldPercentInsiders\": 0.00072999997,\n            \"nextFiscalYearEnd\": 1601337600,\n            \"yield\": null,\n            \"mostRecentQuarter\": 1538179200,\n            \"shortRatio\": 1,\n            \"sharesShortPreviousMonthDate\": \"2018-10-31\",\n            \"floatShares\": 4489763410,\n            \"beta\": 1.127094,\n            \"enterpriseValue\": 789555511296,\n            \"priceHint\": 2,\n            \"threeYearAverageReturn\": null,\n            \"lastSplitDate\": \"2014-06-09\",\n            \"lastSplitFactor\": \"1/7\",\n            \"legalType\": null,\n            \"morningStarOverallRating\": null,\n            \"earningsQuarterlyGrowth\": 0.318,\n            \"priceToSalesTrailing12Months\": null,\n            \"dateShortInterest\": 1543536000,\n            \"pegRatio\": 0.98,\n            \"ytdReturn\": null,\n            \"forwardPE\": 11.289103,\n            \"maxAge\": 1,\n            \"lastCapGain\": null,\n            \"shortPercentOfFloat\": 0.0088,\n            \"sharesShortPriorMonth\": 36469092,\n            \"category\": null,\n            \"fiveYearAverageReturn\": null\n        }\n    }\n\n12. Apple and Wells Fargo Daily Dividend Data:\n\n\n.. code-block:: python\n\n    start_date = '1987-09-15'\n    end_date = '1988-09-15'\n    yahoo_financials = YahooFinancials(['AAPL', 'WFC'])\n    print(yahoo_financials.get_daily_dividend_data(start_date, end_date))\n\n\n.. code-block:: javascript\n\n    {\n        \"AAPL\": [\n            {\n                \"date\": 564157800,\n                \"formatted_date\": \"1987-11-17\",\n                \"amount\": 0.08\n            },\n            {\n                \"date\": 571674600,\n                \"formatted_date\": \"1988-02-12\",\n                \"amount\": 0.08\n            },\n            {\n                \"date\": 579792600,\n                \"formatted_date\": \"1988-05-16\",\n                \"amount\": 0.08\n            },\n            {\n                \"date\": 587655000,\n                \"formatted_date\": \"1988-08-15\",\n                \"amount\": 0.08\n            }\n        ],\n        \"WFC\": [\n            {\n                \"date\": 562861800,\n                \"formatted_date\": \"1987-11-02\",\n                \"amount\": 0.3008\n            },\n            {\n                \"date\": 570724200,\n                \"formatted_date\": \"1988-02-01\",\n                \"amount\": 0.3008\n            },\n            {\n                \"date\": 578583000,\n                \"formatted_date\": \"1988-05-02\",\n                \"amount\": 0.3344\n            },\n            {\n                \"date\": 586445400,\n                \"formatted_date\": \"1988-08-01\",\n                \"amount\": 0.3344\n            }\n        ]\n    }\n\n13. Apple key Financial Data:\n\n\n.. code-block:: python\n\n    yahoo_financials = YahooFinancials(\"AAPL\")\n    print(yahoo_financials.get_financial_data())\n\n\n.. code-block:: javascript\n\n    {\n        'AAPL': {\n            'ebitdaMargins': 0.29395,\n            'profitMargins': 0.21238,\n            'grossMargins': 0.37818,\n            'operatingCashflow': 69390999552,\n            'revenueGrowth': 0.018,\n            'operatingMargins': 0.24572,\n            'ebitda': 76476997632,\n            'targetLowPrice': 150,\n            'recommendationKey': 'buy',\n            'grossProfits': 98392000000,\n            'freeCashflow': 42914250752,\n            'targetMedianPrice': 270,\n            'currentPrice': 261.78,\n            'earningsGrowth': 0.039,\n            'currentRatio': 1.54,\n            'returnOnAssets': 0.11347,\n            'numberOfAnalystOpinions': 40,\n            'targetMeanPrice': 255.51,\n            'debtToEquity': 119.405,\n            'returnOnEquity': 0.55917,\n            'targetHighPrice': 300,\n            'totalCash': 100556996608,\n            'totalDebt': 108046999552,\n            'totalRevenue': 260174004224,\n            'totalCashPerShare': 22.631,\n            'financialCurrency': 'USD',\n            'maxAge': 86400,\n            'revenuePerShare': 56.341,\n            'quickRatio': 1.384,\n            'recommendationMean': 2.2\n        }\n    }\n\n\n",
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