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https://github.com/JECSand/yahoofinancials

A powerful financial data module used for pulling data from Yahoo Finance. This module can pull fundamental and technical data for stocks, indexes, currencies, cryptos, ETFs, Mutual Funds, U.S. Treasuries, and commodity futures.
https://github.com/JECSand/yahoofinancials

bonds commodities cryptocurrencies etfs financial-data forex fundamentals mutual-funds stock-data stock-quotes yahoo-finance

Last synced: 3 months ago
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Host: GitHub
URL: https://github.com/JECSand/yahoofinancials
Owner: JECSand
License: mit
Created: 2017-10-22T03:10:57.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2024-02-06T14:18:22.000Z (12 months ago)
Last Synced: 2024-10-01T20:18:35.043Z (4 months ago)
Topics: bonds, commodities, cryptocurrencies, etfs, financial-data, forex, fundamentals, mutual-funds, stock-data, stock-quotes, yahoo-finance
Language: Python
Homepage: https://pypi.python.org/pypi/yahoofinancials
Size: 419 KB
Stars: 910
Watchers: 57
Forks: 215
Open Issues: 69
Metadata Files:
- Readme: README.rst
- Changelog: CHANGES
- License: LICENSE

Awesome Lists containing this project

README

===============
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
}
}