Metadata-Version: 1.1
Name: yahoofinancials
Version: 1.19
Summary: A powerful financial data module used for pulling both fundamental and technical data from Yahoo Finance
Home-page: https://github.com/JECSand/yahoofinancials
Author: Connor Sanders
Author-email: connor@exceleri.com
License: MIT
Download-URL: https://github.com/JECSand/yahoofinancials/archive/1.19.tar.gz
Description-Content-Type: UNKNOWN
Description: ===============
        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: v1.19
        
        Version Released: 12/12/2023
        
        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.
        
        - 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)
        
        - New methods in Version 1.13:
            - get_esg_score_data()
        
        
        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 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11 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_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
                }
            }
        
Keywords: finance data,stocks,commodities,cryptocurrencies,currencies,forex,yahoo finance
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
