{
    "info": {
        "author": "Connor Sanders",
        "author_email": "connor@exceleri.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Financial and Insurance Industry",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Office/Business :: Financial :: Investment",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "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://travis-ci.org/JECSand/yahoofinancials.svg?branch=master\n    :target: https://travis-ci.org/JECSand/yahoofinancials\n\nCurrent Version: v1.5\n\nVersion Released: 01/27/2019\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- As of Version 0.10, Yahoo Financials now returns historical pricing data for commodity futures, cryptocurrencies, ETFs, mutual funds, U.S. Treasuries, currencies, indexes, and stocks.\n\nInstallation\n-------------\n- yahoofinancials runs on Python 2.7, 3.3, 3.4, 3.5, 3.6, and 3.7.\n- The package depends on beautifulsoup4 and pytz to work.\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 2.7, 3.3, 3.4, 3.5, 3.6, and 3.7 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\n   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.\n3. get_stock_earnings_data(reformat=True)\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\nMethods Added in V1.5\n^^^^^^^^^^^^^^^^^^^^^^^\n- get_daily_dividend_data(start_date, end_date)\n\nAdditional Module Methods\n^^^^^^^^^^^^^^^^^^^^^^^^^\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_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_three_month_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\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\n",
        "description_content_type": "",
        "docs_url": null,
        "download_url": "https://github.com/JECSand/yahoofinancials/archive/1.5.tar.gz",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/JECSand/yahoofinancials",
        "keywords": "finance data",
        "license": "MIT",
        "maintainer": "",
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