Metadata-Version: 2.1
Name: equities
Version: 4.2.7
Summary: equities aims to democratize access to public company data.
Home-page: https://github.com/ljc-codes/equities.git
Author: Tiger_Shark
Author-email: ljwcharles@gmail.com
License: UNKNOWN
Description: # 🐋 equities 
        
        
        --------------------------------------------------------------------------------------------------------------------
        
        Democratizing Access to U.S. Public Company Data
        
        --------------------------------------------------------------------------------------------------------------------
        
        ## Overview: 
        
        **equities** is an intuitive package for accessing high fidelity public company financial data. 
            
        **equities** takes the approach of composing already existing stable and highly maintained libraries and apis. 
        
        All data is served back to the user as dictionary objects or **pandas** dataframes. 
        
        ###### Data Sources: 
        
            Financial Statements:
            Sec Xbrl Financial Statement Data:
                - https://www.sec.gov/dera/data/financial-statement-data-sets.html
        
            Prices, Recommendations, Major Holders, etc:
            Yfinance Pypi Package
                - https://pypi.org/project/yfinance/
        
            Trend Data
            pytrends Pypi Package
                - https://pypi.org/project/pytrends/
        
        ## Install: 
        
            pip3 install equities
        
        ## TUTORIAL: 
        
        #### Instantiating a Universe
        
        We begin by initializing a universe client.
        
            from equities import Universe
            u = Universe(verbose=True)
        
        The verbose optional argument defaults to False. 
        The results of initializing with the verbose=True looks something like this: 
        
            ----------------------------------------
            🐋	Welcome to equities.
            ----------------------------------------
            Initializing Universe...
            > ✨	Auth success. apis connected.
            > 🌌	Universe initialized. size: 7896
            Success. You're good to go!
            ----------------------------------------
        
        
        #### Essential Methods 
        
        To get the number of companies in the universe call: 
        
            len(u)
        
        "CIK" numbers are the sec's official unique identifier for public companies. It stands for "Central Index Key" A full list of the cik numbers in the universe is found in:
        
            u.ciks
        
        Similarly, if we want the names of companies in the universe we can call: 
        
            u.names
        
        Finally, to get tickers we call:
        
            u.tickers
        
        To get a dictionary mapping "cik" numbers to the names of companies execute:
        
            u.cik_to_name()
        
        We can get get a map of cik numbers to tickers through :
        
            u.cik_to_ticker()
        
        
        The inverses of both of these dictionaries are also accessible through u.name_to_cik() and u.ticker_to_cik()
        
        ## Search: 
        
        You can search for companies by names, ticker or ciks by using the search function. Note that in all universe queries handle for case and whitespace.
        
            u.search("netflix")
        
        Here are the results of this query.
        
            > 🛰️     Search query: "netflix" found 1 matches.
            {'NETFLIX INC': '1065280'}
        
        Let's find the ticker of this company. 
        
            u.cik_to_ticker()['1065280']
        
        Here are results:
        
            'nflx'
        
        ## Queries: 
        
        #### Company 
        
        company data can be obtained by passing a "cik" or "ticker" into the "company()" function on the universe. 
            
            u.company('nflx')
            
            # We can also pass in a query like this: u.company("Netflix",search=True). 
            # It returns the first result of the search query. 
            # for multithreaded bunk downloads, we can supply a list of queries to the function.
            # for example: u.company(u.ciks)
        
        The above requests for netflix data returns a dictionary. Here are it's keys: 
        
            dict_keys(
                ['name',
                 'sic',
                 'business_address',
                 'mailing_address',
                 'phone',
                 'country_incorporated',
                 'state_incorporated', 
                 'ein',
                 'former_name',
                 'income',
                 'balance',
                 'cash',
                 'equity',
                 'prices',
                 'actions',
                 'dividends',
                 'splits',
                 'major_holders',
                 'institutional_holders',
                 'events',
                 'recommendations',
                 'esg']
            )
        
        Now see below the full response from the request.
        
         Observe that the keys, "income","balance","cash","equity" are dataframes and encode the income statement, balance sheet, cashflow statement and equity statement respectively of the company in question. Other keys also map to dataframes for example "prices" and "institutional holders". Naming conventions and structure is chosen for simplicity. 
        
            > 📦    Fetching company: 1065280 ...
            {
                "name " : " NETFLIX INC ",
                "sic " : " 7841.0 ",
                "business_address " :  
                    {
                        'country': 'US',
                        'city': 'LOS GATOS',
                        'zip': '95032',
                        'adr1': '100 WINCHESTER CIRCLE',
                        'adr2': '.'
                    },
                "mailing_address " : 
                    {
                        'country': 'US',
                        'city': 'LOS GATOS',
                        'zip': '95032-7606',
                        'adr1': '100 WINCHESTER CIRCLE',
                        'adr2': 'nan',
                        'state': 'CA'
                    },
                "phone " : "408-540-3700 ",
                "country_incorporated " : " US ",
                "state_incorporated " : " DE ",
                "ein " : " 770467272.0 ",
                "former_name " : " NETFLIX COM INC ",
                    "income " :                                                     2009q2 2009q3 2009q4 2010q1 2010q2  ...        2019q2        2019q3        2019q4        2020q2        2020q3
                    Revenues                                             None   None   None   None   None  ...  3.700856e+09  3.907270e+09  3.999374e+09  5.767691e+09  6.148286e+09
                    CostOfRevenue                                        None   None   None   None   None  ...  2.300579e+09  5.876271e+09  8.974190e+09  2.870614e+09  3.643707e+09
                    MarketingExpense                                     None   None   None   None   None  ...  6.165780e+08  5.920070e+08  5.103300e+08  5.038300e+08  1.219728e+09
                    ResearchAndDevelopmentExpense                        None   None   None   None   None  ...  2.823100e+08  5.814050e+08  8.900250e+08  4.538170e+08  3.832330e+08
                    GeneralAndAdministrativeExpense                      None   None   None   None   None  ...  2.019520e+08  1.515240e+08  1.686280e+08  2.520870e+08  2.246570e+08
                    OperatingIncomeLoss                                  None   None   None   None   None  ...  4.465780e+08  4.622130e+08  4.806680e+08  4.590840e+08  7.064190e+08
                    InterestExpense                                      None   None   None   None   None  ...  1.355290e+08  2.875620e+08  4.482220e+08  1.355290e+08  1.891510e+08
                    NonoperatingIncomeExpense                            None   None   None   None   None  ...  7.610400e+07  6.802800e+07  7.004000e+06  2.169700e+07  2.263400e+07
                    IncomeLossFromContinuingOperationsBeforeIncomeT...   None   None   None   None   None  ...  3.996590e+08  7.282520e+08  1.107062e+09  7.958700e+08  9.005750e+08
                    IncomeTaxExpenseBenefit                              None   None   None   None   None  ...  9.492000e+06  4.428700e+07  6.329520e+08  8.680300e+07  3.154060e+08
                    NetIncomeLoss                                        None   None   None   None   None  ...  2.901240e+08  3.843490e+08  4.028350e+08  3.440520e+08  2.706500e+08
                    EarningsPerShareBasic                                None   None   None   None   None  ...  7.900000e-01  8.800000e-01  9.200000e-01  7.900000e-01  6.200000e-01
                    EarningsPerShareDiluted                              None   None   None   None   None  ...  7.600000e-01  1.360000e+00  2.830000e+00  7.600000e-01  1.360000e+00
                    WeightedAverageNumberOfSharesOutstandingBasic        None   None   None   None   None  ...  4.341740e+08  4.375870e+08  4.380900e+08  4.369470e+08  4.375870e+08
                    WeightedAverageNumberOfDilutedSharesOutstanding      None   None   None   None   None  ...  4.503590e+08  4.520630e+08  4.518960e+08  4.519220e+08  4.520630e+08
                    GainsLossesOnExtinguishmentOfDebt                    None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    OtherNonoperatingIncome                              None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    CostOfGoodsSoldSubscription                          None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    FulfillmentExpense                                   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    GrossProfit                                          None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    OperatingExpenses                                    None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    TechnologyandDevelopmentExpense                      None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
        
                    [22 rows x 44 columns] ,
                    "balance " :                                                  2009q2 2009q3 2009q4 2010q1 2010q2  ...        2019q2        2019q3        2019q4        2020q2        2020q3
                    CommonStockParOrStatedValuePerShare               None   None   None   None   None  ...  1.000000e-03  1.000000e-03  1.000000e-03  1.000000e-03  1.000000e-03
                    CommonStockSharesAuthorized                       None   None   None   None   None  ...  4.990000e+09  4.990000e+09  4.990000e+09  4.990000e+09  4.990000e+09
                    CommonStockSharesIssued                           None   None   None   None   None  ...  4.365986e+08  4.378349e+08  4.382513e+08  4.397806e+08  4.410154e+08
                    CashAndCashEquivalentsAtCarryingValue             None   None   None   None   None  ...  3.794483e+09  3.794483e+09  3.794483e+09  5.151884e+09  7.153248e+09
                    AvailableForSaleSecuritiesCurrent                 None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    CommonStockSharesOutstanding                      None   None   None   None   None  ...  4.365986e+08  4.365986e+08  4.382513e+08  4.397806e+08  4.388066e+08
                    ContentAssetsNetCurrent                           None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    OtherAssetsCurrent                                None   None   None   None   None  ...  8.203500e+08  7.484660e+08  7.484660e+08  1.295897e+09  1.160067e+09
                    AssetsCurrent                                     None   None   None   None   None  ...  9.694135e+09  9.694135e+09  9.694135e+09  6.178504e+09  8.564139e+09
                    ContentAssetsNetNoncurrent                        None   None   None   None   None  ...  2.088878e+10           NaN  2.323499e+10  2.526689e+10  2.515512e+10
                    PropertyPlantAndEquipmentNet                      None   None   None   None   None  ...  4.343720e+08  4.182810e+08  4.819920e+08  5.652210e+08  7.519410e+08
                    OtherAssetsNoncurrent                             None   None   None   None   None  ...  1.726568e+09  1.896043e+09  9.010300e+08  2.727420e+09  2.727420e+09
                    Assets                                            None   None   None   None   None  ...  2.721863e+10  3.017134e+10  3.094171e+10  3.505991e+10  3.717528e+10
                    ContentLiabilitiesCurrent                         None   None   None   None   None  ...  4.686019e+09           NaN  4.860542e+09  4.413561e+09  4.664733e+09
                    AccountsPayableCurrent                            None   None   None   None   None  ...  5.629850e+08  4.421940e+08  5.629850e+08  6.743470e+08  6.743470e+08
                    AccruedLiabilitiesCurrent                         None   None   None   None   None  ...  4.774170e+08  4.774170e+08  1.037723e+09  8.430430e+08  9.865950e+08
                    DeferredRevenueCurrent                            None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    LiabilitiesCurrent                                None   None   None   None   None  ...  6.487320e+09  6.487320e+09  7.257900e+09  6.855696e+09  6.855696e+09
                    ContentLiabilitiesNoncurrent                      None   None   None   None   None  ...  3.759026e+09           NaN  3.759026e+09  3.206051e+09  3.208164e+09
                    LongTermDebtNoncurrent                            None   None   None   None   None  ...  1.036006e+10  1.036006e+10  1.036006e+10  1.475926e+10  1.475926e+10
                    OtherLiabilitiesNoncurrent                        None   None   None   None   None  ...  1.292310e+08  1.292310e+08  1.292310e+08  1.444276e+09  1.710948e+09
                    Liabilities                                       None   None   None   None   None  ...  2.151557e+10  2.073564e+10  2.408021e+10  2.665062e+10  2.639356e+10
                    CommitmentsAndContingencies                       None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    CommonStockValue                                  None   None   None   None   None  ...  2.315988e+09  2.315988e+09  2.315988e+09  2.793929e+09  2.793929e+09
                    AccumulatedOtherComprehensiveIncomeLossNetOfTax   None   None   None   None   None  ... -1.958200e+07 -1.958200e+07 -1.958200e+07 -2.352100e+07 -3.407200e+07
                    RetainedEarningsAccumulatedDeficit                None   None   None   None   None  ...  3.288885e+09  2.942359e+09  4.224779e+09  5.520816e+09  4.811749e+09
                    StockholdersEquity                                None   None   None   None   None  ...  5.238765e+09  3.581956e+09  3.581956e+09  5.703058e+09  7.582157e+09
                    LiabilitiesAndStockholdersEquity                  None   None   None   None   None  ...  2.597440e+10  2.597440e+10  2.597440e+10  3.505991e+10  3.717528e+10
                    PreferredStockParOrStatedValuePerShare            None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    PreferredStockSharesAuthorized                    None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    PreferredStockSharesIssued                        None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    PreferredStockSharesOutstanding                   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    PreferredStockValue                               None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    ContentLibraryNetCurrent                          None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    PrepaidContentCurrent                             None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    ContentLibraryNetNoncurrent                       None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    DueToRelatedPartiesNoncurrent                     None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    AdditionalPaidInCapitalCommonStock                None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    ContractWithCustomerLiabilityCurrent              None   None   None   None   None  ...  8.086920e+08  7.608990e+08  9.155060e+08  9.247450e+08  1.029261e+09
                    ShortTermBorrowings                               None   None   None   None   None  ...           NaN           NaN           NaN  0.000000e+00  4.991610e+08
                    OtherPrepaidExpenseCurrent                        None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    ContentAccountsPayableCurrent                     None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    ContentAccountsPayableNoncurrent                  None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    SeniorLongTermNotes                               None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    RelatedPartyTransactionDueFromToRelatedParty      None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    LicensingAssetCurrent                             None   None   None   None   None  ...  5.151186e+09           NaN  5.151186e+09           NaN           NaN
        
                    [46 rows x 44 columns] ,
                    "cash " :                                                     2009q2 2009q3 2009q4 2010q1 2010q2  ...        2019q2       2019q3        2019q4        2020q2        2020q3
                    NetIncomeLoss                                        None   None   None   None   None  ...  2.901240e+08  384349000.0  4.028350e+08  7.090670e+08  2.706500e+08
                    AdditionstoStreamingContentAssets                    None   None   None   None   None  ...  2.997746e+09          NaN  9.971141e+09  3.294275e+09  2.510782e+09
                    ChangeInStreamingContentLiabilities                  None   None   None   None   None  ... -1.469800e+07          NaN -9.554800e+07  2.589450e+08 -1.084320e+08
                    CostofServicesAmortizationofStreamingContentAssets   None   None   None   None   None  ...  2.124686e+09          NaN  1.911767e+09  2.483385e+09  4.356601e+09
                    CostofServicesAmortizationofDVDContentAssets         None   None   None   None   None  ...  8.509000e+06          NaN  2.281900e+07           NaN           NaN
                    ...                                                   ...    ...    ...    ...    ...  ...           ...          ...           ...           ...           ...
                    ProceedsFromSaleOfAvailableForSaleSecuritiesDebt     None   None   None   None   None  ...           NaN          NaN           NaN           NaN           NaN
                    InterestPaidNet                                      None   None   None   None   None  ...           NaN          NaN           NaN           NaN           NaN
                    ProceedsfromPublicOfferingofCommonStock              None   None   None   None   None  ...           NaN          NaN           NaN           NaN           NaN
                    ExtinguishmentOfDebtAmount                           None   None   None   None   None  ...           NaN          NaN           NaN           NaN           NaN
                    ForeignCurrencyTransactionLossBeforeTax              None   None   None   None   None  ...           NaN          NaN           NaN           NaN           NaN
        
                    [71 rows x 44 columns] ,
                    "equity " :                                                     2009q2 2009q3 2009q4 2010q1 2010q2  ...        2019q2        2019q3        2019q4        2020q2        2020q3
                    NetIncomeLoss                                        None   None   None   None   None  ...  3.440520e+08  6.147020e+08  1.279946e+09  3.440520e+08  2.706500e+08
                    OtherComprehensiveIncomeLossNetOfTaxPortionAttr...   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockIssuedDuringPeriodSharesStockOptionsExercised   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockIssuedDuringPeriodValueStockOptionsExercised    None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockIssuedDuringPeriodSharesConversionOfConver...   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockIssuedDuringPeriodValueConversionOfConvert...   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    AdjustmentsToAdditionalPaidInCapitalSharebasedC...   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    AdjustmentsToAdditionalPaidInCapitalTaxEffectFr...   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockholdersEquity                                   None   None   None   None   None  ...  5.703058e+09  6.105548e+09  6.861505e+09  5.703058e+09  6.105548e+09
                    ComprehensiveIncomeNetOfTax                          None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockIssuedDuringPeriodValueEmployeeStockPurcha...   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockIssuedDuringPeriodValueNewIssues                None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockRepurchasedAndRetiredDuringPeriodValue          None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockRepurchasedAndRetiredDuringPeriodShares         None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    CumulativeEffectOfNewAccountingPrincipleInPerio...   None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
                    StockIssuedDuringPeriodSharesNewIssues               None   None   None   None   None  ...           NaN           NaN           NaN           NaN           NaN
        
                    [16 rows x 44 columns] ,
                    "prices " :                    Open        High         Low       Close     Volume  Dividends  Stock Splits
                    Date                                                                                          
                    2002-05-23    1.156429    1.242857    1.145714    1.196429  104790000          0           0.0
                    2002-05-24    1.214286    1.225000    1.197143    1.210000   11104800          0           0.0
                    2002-05-28    1.213571    1.232143    1.157143    1.157143    6609400          0           0.0
                    2002-05-29    1.164286    1.164286    1.085714    1.103571    6757800          0           0.0
                    2002-05-30    1.107857    1.107857    1.071429    1.071429   10154200          0           0.0
                    ...                ...         ...         ...         ...        ...        ...           ...
                    2020-10-21  501.029999  506.850006  488.250000  489.049988   17405700          0           0.0
                    2020-10-22  494.690002  495.140015  482.000000  485.230011    6997900          0           0.0
                    2020-10-23  488.109985  490.059998  481.350006  488.279999    4927900          0           0.0
                    2020-10-26  487.029999  496.820007  478.899994  488.239990    6174200          0           0.0
                    2020-10-27  490.010010  490.000000  482.929993  488.929993    3547975          0           0.0
        
                    [4641 rows x 7 columns] ,
                "actions " :              Dividends  Stock Splits
                    Date                               
                    2004-02-12        0.0           2.0
                    2015-07-15        0.0           7.0 ",
                "dividends " : " Series([], Name: Dividends, dtype: int64) ",
                "splits " : " Date
                    2004-02-12    2.0
                    2015-07-15    7.0
                    Name: Stock Splits, dtype: float64 ",
                "major_holders " : "         0                                      1
                    0   1.62%        % of Shares Held by All Insider
                    1  83.49%       % of Shares Held by Institutions
                    2  84.86%        % of Float Held by Institutions
                    3    1975  Number of Institutions Holding Shares ",
                    "institutional_holders " : "                               Holder    Shares Date Reported   % Out        Value
                    0  Capital Research Global Investors  34111988    2020-06-29  0.0772  15522319019
                    1         Vanguard Group, Inc. (The)  34001284    2020-06-29  0.0770  15471944271
                    2                     Blackrock Inc.  29171135    2020-06-29  0.0660  13274033270
                    3                           FMR, LLC  22033243    2020-06-29  0.0499  10026006894
                    4      Price (T.Rowe) Associates Inc  20626346    2020-06-29  0.0467   9385812483
                    5           State Street Corporation  16613245    2020-06-29  0.0376   7559691004
                    6    Capital International Investors  15137030    2020-06-29  0.0343   6887954131
                    7            Capital World Investors  13676170    2020-06-29  0.0310   6223204396
                    8            Jennison Associates LLC   9099165    2020-06-29  0.0206   4140484041
                    9        Baillie Gifford and Company   7713485    2020-06-29  0.0175   3509944214 ,
                "events " :                                      0                    1
                    Earnings Date     2021-01-19 00:00:00  2021-01-25 00:00:00
                    Earnings Average                 2.13                 2.13
                    Earnings Low                     1.82                 1.82
                    Earnings High                     2.3                  2.3
                    Revenue Average            6379370000           6379370000
                    Revenue Low                6281000000           6281000000
                    Revenue High               6593000000           6593000000 ",
                    "recommendations " : "                                     0                    1
                    Earnings Date     2021-01-19 00:00:00  2021-01-25 00:00:00
                    Earnings Average                 2.13                 2.13
                    Earnings Low                     1.82                 1.82
                    Earnings High                     2.3                  2.3
                    Revenue Average            6379370000           6379370000
                    Revenue Low                6281000000           6281000000
                    Revenue High               6593000000           6593000000 ",
                    "esg " : "                             Value
                    2020-10                          
                    palmOil                     False
                    controversialWeapons        False
                    gambling                    False
                    socialScore                  7.56
                    nuclear                     False
                    furLeather                  False
                    alcoholic                   False
                    gmo                         False
                    catholic                    False
                    socialPercentile             None
                    peerCount                      44
                    governanceScore             10.32
                    environmentPercentile        None
                    animalTesting               False
                    tobacco                     False
                    totalEsg                    18.05
                    highestControversy              2
                    esgPerformance         UNDER_PERF
                    coal                        False
                    pesticides                  False
                    adult                       False
                    percentile                   14.5
                    peerGroup                   Media
                    smallArms                   False
                    environmentScore             0.16
                    governancePercentile         None
                    militaryContract            False, 
                "interest":             NETFLIX INC isPartial
                    date                             
                    2015-11-22           57     False
                    2015-11-29           47     False
                    2015-12-06           45     False
                    2015-12-13           39     False
                    2015-12-20           32     False
                    ...                 ...       ...
                    2020-10-18           69     False
                    2020-10-25           57     False
                    2020-11-01           55     False
                    2020-11-08           63     False
                    2020-11-15           73      True
        
                    [261 rows x 2 columns]}
            }
            
        
        #### Sub Functions
        
        The previous request pulls all data about a given company. This is obviously resource intensive. If you would like to request some subset of the full request, we advise using subfunctions. The following is a list of all available subfunctions.
        
            u.prices(cik_or_ticker)                                 # prices,volume, splits dataframe
        
            u.dividends(cik_or_ticker)                              # dividend payouts dataframe
        
            u.financial_statement(cik_or_ticker,kind="income")      # income statement dataframe
        
            u.financial_statement(cik_or_ticker,kind="balance")     # balance sheet dataframe
        
            u.financial_statement(cik_or_ticker,"cash")             # cashflow statement dataframe
        
            u.major_sharholders(cik_or_ticker)                      # major shareholders dataframe
        
            u.major_sharholders(cik_or_ticker)                      # major shareholders dataframe
        
            u.institutional_holders(cik_or_ticker")                 # institutional holders dataframe
        
            u.events(cik_or_ticker)                                 # date of events dataframe
        
            u.splits(cik_or_ticker)                                 # stock split events dataframe
        
            u.recommendations(cik_or_ticker)                        # analyst recommendations dataframe
        
            u.esg(cik_or_ticker)                                    # esg metrics dataframe
        
            u.interest(name)                                        # google trends dataframe
        
        
        #### Example Use Case 
        
        I really want to demonstrate the beauty of what we have here since this is often difficult when
        looking at thousands of numeric datatables. Let's take a very naive peek by plotting various 
        dataframes as timeseries. 
        
        The following is a start to finish example of how one might plot the financial statements and price 
        series of the first five companies in the universe.
        
        Here's how we'd implement that: 
        
            from equities import Universe
            import matplotlib.pyplot as plt 
        
            u = Universe()
        
            k,f,s = 'bar',(10,7),True
            for cik in u.ciks[:5]:
        
                c = u.company(cik)
        
                income = c['income']
                if not income.empty:
                    income.T.plot(
                    kind=k,
                    figsize=f,
                    stacked=s)
        
                balance = c['balance']
                if not balance.empty:
                    balance.T.plot(
                    kind=k,
                    figsize=f,
                    stacked=s) 
        
                cash = c['cash']
                if not cash.empty:
                    cash.T.plot(
                    kind=k,
                    figsize=f,
                    stacked=s)
        
                prices = c['prices']
                if not prices.empty:
                    prices.drop('Volume',axis=1).plot(
                        kind='line',
                        figsize=f)
        
                # Notice that the code above is expensive since we are interested in a few fields
                # within the results "c", using sub functions would be much more efficient.
        
            plt.show()
        
        ## Donate:
        
        Consider buying me a coffee to fund the future development of this project.
        
            bitcoin wallet address: 3LU5MEaAXRJoCo6vx67g1Jj7qDFRKhMs5t
Keywords: sec stock stockmarket equities equity data financials financial company public companies xbrl
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
