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<li class="toctree-l1 current"><a class="current reference internal" href="#">Angler API</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#install-import-and-initialization">Install, Import, and Initialization</a></li>
<li class="toctree-l2"><a class="reference internal" href="#angler-functions">Angler Functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#angler-querycik-ticker"><em>Angler.queryCIK(ticker)</em></a></li>
<li class="toctree-l3"><a class="reference internal" href="#angler-queryname-self-ticker-or-cik"><em>Angler.queryName(self, ticker_or_CIK)</em></a></li>
<li class="toctree-l3"><a class="reference internal" href="#angler-query10k-self-ticker-or-cik-years"><em>Angler.query10K(self, ticker_or_CIK, years)</em></a></li>
<li class="toctree-l3"><a class="reference internal" href="#angler-query10q-self-ticker-or-cik-periods"><em>Angler.query10Q(self, ticker_or_CIK, periods)</em></a></li>
<li class="toctree-l3"><a class="reference internal" href="#angler-query-self-command"><em>Angler.query(self, command)</em></a></li>
<li class="toctree-l3"><a class="reference internal" href="#angler-dispose-self"><em>Angler.dispose(self)</em></a></li>
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<li class="toctree-l3"><a class="reference internal" href="#form-filter-self-regex-index-tag"><em>Form.filter(self, regex, index=’tag’)</em></a></li>
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<div class="section" id="angler-api">
<h1>Angler API<a class="headerlink" href="#angler-api" title="Permalink to this headline">¶</a></h1>
<p>Angler is a SEC financial data analysis tool provided by Blacktip Research.
You must make an account on the <a class="reference external" href="http://blacktipresearch.com">Blacktip website</a> prior to use.</p>
<div class="section" id="install-import-and-initialization">
<h2>Install, Import, and Initialization<a class="headerlink" href="#install-import-and-initialization" title="Permalink to this headline">¶</a></h2>
<p>You can find Angler on <a class="reference external" href="https://pypi.org/project/blacktip/">PyPI</a>, and can install via the
terminal using <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">blacktip</span></code>. To import Angler in a file, do the following:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> from blacktip.angler import Angler
>>> instance = Angler(username, password)
</pre></div>
</div>
<p>Replace <code class="docutils literal notranslate"><span class="pre">username</span></code> and <code class="docutils literal notranslate"><span class="pre">password</span></code> with your personal login credentials.</p>
</div>
<div class="section" id="angler-functions">
<h2>Angler Functions<a class="headerlink" href="#angler-functions" title="Permalink to this headline">¶</a></h2>
<p><strong>The querying object.</strong> Angler provides several querying functions to interface with the database.</p>
<div class="section" id="angler-querycik-ticker">
<h3><em>Angler.queryCIK(ticker)</em><a class="headerlink" href="#angler-querycik-ticker" title="Permalink to this headline">¶</a></h3>
<p>Get the CIK (central index key) of an inputted ticker.</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>ticker : string</strong></p>
<ul>
<li><p>the ticker for which to search the corresponding CIK</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>tuple</strong></p>
<ul>
<li><p>a tuple containing (ticker, CIK) as strings</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> Angler.queryCIK("AAPL")
('AAPL', '320193')
</pre></div>
</div>
</div>
<div class="section" id="angler-queryname-self-ticker-or-cik">
<h3><em>Angler.queryName(self, ticker_or_CIK)</em><a class="headerlink" href="#angler-queryname-self-ticker-or-cik" title="Permalink to this headline">¶</a></h3>
<p>Get the name of a company from its ticker or CIK number.</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>ticker_or_CIK : string or int</strong></p>
<ul>
<li><p>the ticker or CIK number of the company</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>string</strong></p>
<ul>
<li><p>the name of the company</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> instance.queryName("AAPL")
'APPLE INC'
>>> instance.queryName(320193)
'APPLE INC'
</pre></div>
</div>
</div>
<div class="section" id="angler-query10k-self-ticker-or-cik-years">
<h3><em>Angler.query10K(self, ticker_or_CIK, years)</em><a class="headerlink" href="#angler-query10k-self-ticker-or-cik-years" title="Permalink to this headline">¶</a></h3>
<p>Get company 10-K reports for selected years.</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>ticker_or_CIK : string or int</strong></p>
<ul>
<li><p>the ticker or CIK number of the company</p></li>
</ul>
</li>
<li><p><strong>years : int or iterable</strong></p>
<ul>
<li><p>the year or years of interest</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>Form10K</strong></p>
<ul>
<li><p>returns a Form10K object with the selected query</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form10K = instance.query10K("AAPL", [2018, 2019])
>>> print(form10K)
fy 2018 2019
tag uom
AccountsPayableCurrent USD 4.424200e+10 4.623600e+10
AccountsReceivableNetCurrent USD 1.787400e+10 2.292600e+10
AccruedIncomeTaxesNoncurrent USD 2.570000e+08 3.358900e+10
AccumulatedDepreciationDepletionAndAmortization... USD 4.129300e+10 4.909900e+10
AccumulatedOtherComprehensiveIncomeLossNetOfTax USD -1.500000e+08 -5.840000e+08
... ... ...
UnrecordedUnconditionalPurchaseObligationBalanc... USD 9.328000e+09 8.211000e+09
UnrecordedUnconditionalPurchaseObligationDueAft... USD 6.600000e+07 1.100000e+08
WeightedAverageNumberDilutedSharesOutstandingAd... shares 2.946100e+07 3.445000e+07
WeightedAverageNumberOfDilutedSharesOutstanding shares 5.500281e+09 5.251692e+09
WeightedAverageNumberOfSharesOutstandingBasic shares 5.470820e+09 5.217242e+09
</pre></div>
</div>
</div>
<div class="section" id="angler-query10q-self-ticker-or-cik-periods">
<h3><em>Angler.query10Q(self, ticker_or_CIK, periods)</em><a class="headerlink" href="#angler-query10q-self-ticker-or-cik-periods" title="Permalink to this headline">¶</a></h3>
<p>Get company 10-Q reports for selected periods.</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>ticker_or_CIK : string or int</strong></p>
<ul>
<li><p>the ticker or CIK number of the company</p></li>
</ul>
</li>
<li><p><strong>periods : int or iterable of ints, tuple or iterable of tuples</strong></p>
<ul>
<li><p>the periods of interest in (year, quarter) format</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>Form10Q</strong></p>
<ul>
<li><p>returns a Form10Q object with the selected query</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span># the following commands are equivalent Angler.query10Q() calls
>>> instance.query10Q("AAPL", 2019)
>>> instance.query10Q("AAPL", [(2019, "Q1"), (2019, "Q2"), (2019, "Q3")])
fy 2019
fp Q1 Q2 Q3
tag uom
AccountsPayableCurrent USD 5.588800e+10 3.044300e+10 5.588800e+10
AccountsReceivableNetCurrent USD 2.318600e+10 1.508500e+10 2.318600e+10
AccruedIncomeTaxesNoncurrent USD 3.358900e+10 3.098600e+10 3.358900e+10
AccumulatedDepreciationDepletionAndAmortization... USD 4.909900e+10 5.429000e+10 4.909900e+10
AccumulatedOtherComprehensiveIncomeLossNetOfTax USD -3.454000e+09 -1.499000e+09 -6.390000e+08
... ... ... ...
UnrecognizedTaxBenefitsThatWouldImpactEffective... USD 8.200000e+09 7.300000e+09 8.100000e+09
UnrecordedUnconditionalPurchaseObligationBalanc... USD 7.400000e+09 7.600000e+09 8.100000e+09
WeightedAverageNumberDilutedSharesOutstandingAd... shares 4.491000e+07 2.657500e+07 3.074700e+07
WeightedAverageNumberOfDilutedSharesOutstanding shares 5.157787e+09 4.700646e+09 4.601380e+09
WeightedAverageNumberOfSharesOutstandingBasic shares 5.112877e+09 4.704945e+09 4.660175e+09
</pre></div>
</div>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span># additionally, one can query multiple years
>>> instance.query10Q("AAPL", [2018, 2019])
fy 2018 ... 2019
fp Q1 Q2 ... Q2 Q3
tag uom ...
AccountsPayableCurrent USD 6.298500e+10 4.904900e+10 ... 3.044300e+10 5.588800e+10
AccountsReceivableNetCurrent USD 2.344000e+10 1.787400e+10 ... 1.508500e+10 2.318600e+10
AccruedIncomeTaxesNoncurrent USD 3.491300e+10 2.570000e+08 ... 3.098600e+10 3.358900e+10
AccruedLiabilitiesCurrent USD 2.574400e+10 2.574400e+10 ... NaN NaN
AccumulatedDepreciationDepletionAndAmortization... USD 4.129300e+10 4.129300e+10 ... 5.429000e+10 4.909900e+10
... ... ... ... ... ...
UnrecognizedTaxBenefitsThatWouldImpactEffective... USD 7.700000e+09 8.200000e+09 ... 7.300000e+09 8.100000e+09
UnrecordedUnconditionalPurchaseObligationBalanc... USD 8.700000e+09 8.300000e+09 ... 7.600000e+09 8.100000e+09
WeightedAverageNumberDilutedSharesOutstandingAd... shares 2.933400e+07 3.589700e+07 ... 2.657500e+07 3.074700e+07
WeightedAverageNumberOfDilutedSharesOutstanding shares 5.327995e+09 5.261688e+09 ... 4.700646e+09 4.601380e+09
WeightedAverageNumberOfSharesOutstandingBasic shares 5.298661e+09 5.225791e+09 ... 4.704945e+09 4.660175e+09
</pre></div>
</div>
</div>
<div class="section" id="angler-query-self-command">
<h3><em>Angler.query(self, command)</em><a class="headerlink" href="#angler-query-self-command" title="Permalink to this headline">¶</a></h3>
<p>Query your own custom command on the XBRL dataset in MySQL format.</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>command : string</strong></p>
<ul>
<li><p>the command string</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>SQLAlchemy.engine.ResultProxy</strong></p>
<ul>
<li><p>the query result</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> _, cik = Angler.queryCIK("aapl")
>>> command = "SELECT * FROM sub WHERE cik={cik}".format(cik=cik)
>>> instance.query(command).first()
('0000320193-17-000009', Decimal('320193'), 'APPLE INC', Decimal('3571'), 'US', 'CA', 'CUPERTINO', '95014', 'ONE INFINITE LOOP', '', '(408) 996-10', 'US', 'CA', 'CUPERTINO', '95014', 'ONE INFINITE LOOP', '', 'US', 'CA', Decimal('942404110'), 'APPLE COMPUTER INC', '19970808', '1-LAF', 0, '0930', '10-Q', datetime.date(2017, 6, 30), 2017, 'Q3', datetime.date(2017, 8, 2), datetime.datetime(2017, 8, 2, 16, 31), 0, 1, 'aapl-20170701.xml', Decimal('1'), '', '2017q3')
</pre></div>
</div>
</div>
<div class="section" id="angler-dispose-self">
<h3><em>Angler.dispose(self)</em><a class="headerlink" href="#angler-dispose-self" title="Permalink to this headline">¶</a></h3>
<p>Closes the connection to the database.</p>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> instance.dispose()
</pre></div>
</div>
</div>
</div>
<div class="section" id="form-functions">
<h2>Form Functions<a class="headerlink" href="#form-functions" title="Permalink to this headline">¶</a></h2>
<p><strong>The (parent) data manipulation function.</strong> The <strong>Form</strong> object offers some convenient data
manipulation functions that apply to all (10-K and 10-Q) SEC forms. <strong>Form10K</strong> and <strong>Form10Q</strong>
objects are subclasses of <strong>Form</strong> and therefore all <strong>Form</strong> functions apply to them.</p>
<div class="section" id="form-form-self">
<h3><em>Form.form(self)</em><a class="headerlink" href="#form-form-self" title="Permalink to this headline">¶</a></h3>
<p>Returns the contents of the Form object.</p>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>pandas.DataFrame</strong></p>
<ul>
<li><p>the contents of the Form as a pandas dataframs</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form = instance.query10K("AAPL", 2019)
>>> form.form() # returns a Form10K object, a subclass of Form
fy 2019
tag uom
AccountsPayableCurrent USD 4.623600e+10
AccountsReceivableNetCurrent USD 2.292600e+10
AccruedIncomeTaxesNoncurrent USD 2.954500e+10
AccumulatedDepreciationDepletionAndAmortization... USD 5.857900e+10
AccumulatedOtherComprehensiveIncomeLossNetOfTax USD -5.840000e+08
... ...
UnrecordedUnconditionalPurchaseObligationBalanc... USD 8.211000e+09
UnrecordedUnconditionalPurchaseObligationDueAft... USD 1.100000e+08
WeightedAverageNumberDilutedSharesOutstandingAd... shares 3.107900e+07
WeightedAverageNumberOfDilutedSharesOutstanding shares 4.648913e+09
WeightedAverageNumberOfSharesOutstandingBasic shares 4.617834e+09
</pre></div>
</div>
<p>To save your form to csv, use the <strong>Form.form()</strong> function then <strong>pandas.DataFrame.to_csv()</strong>:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> pandas_dataframe = form.form()
>>> pandas_dataframe.to_csv(filepath) # specify filepath to save to
</pre></div>
</div>
<p>Note, one can print and perform basic indexing directly on the <strong>Form</strong> object:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> print(form)
...
>>> print(form[2019])
...
</pre></div>
</div>
</div>
<div class="section" id="form-filter-self-regex-index-tag">
<h3><em>Form.filter(self, regex, index=’tag’)</em><a class="headerlink" href="#form-filter-self-regex-index-tag" title="Permalink to this headline">¶</a></h3>
<p>Filter rows of the form by a specific keyword regular expression (regex).</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>regex : string</strong></p>
<ul>
<li><p>the regular expression to filter the rows by</p></li>
</ul>
</li>
<li><p><strong>index : string</strong></p>
<ul>
<li><p>the index (“tag” or “uom”) to apply the filter to; defaults to “tag”</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>pandas.DataFrame</strong></p>
<ul>
<li><p>a pandas dataframe with the filtered results</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form = instance.query10Q("AAPL", [2018, 2019])
>>> form.filter("^NetIncomeLoss$")
fy 2018 2019
fp Q1 Q2 Q3 Q1 Q2 Q3
tag uom
NetIncomeLoss USD 2.006500e+10 1.382200e+10 1.151900e+10 1.996500e+10 1.156100e+10 1.004400e+10
</pre></div>
</div>
</div>
<div class="section" id="form-asset-sheet-self">
<h3><em>Form.asset_sheet(self)</em><a class="headerlink" href="#form-asset-sheet-self" title="Permalink to this headline">¶</a></h3>
<p>Filters the form to generate an asset sheet. Wrapper around <code class="docutils literal notranslate"><span class="pre">form.filter("Asset|Assets")</span></code>.</p>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>pandas.DataFrame</strong></p>
<ul>
<li><p>a pandas dataframe with just values pertaining to “assets”</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form = instance.query10K("aapl", 2019)
>>> form.asset_sheet()
fy 2019
tag uom
Assets USD 3.385160e+11
AssetsCurrent USD 1.628190e+11
AssetsNoncurrent USD 1.756970e+11
DeferredTaxAssetsDeferredIncome USD 1.372000e+09
DeferredTaxAssetsGoodwillAndIntangibleAssets USD 1.143300e+10
DeferredTaxAssetsLiabilitiesNet USD 8.045000e+09
DeferredTaxAssetsNet USD 1.964000e+10
DeferredTaxAssetsOther USD 6.970000e+08
DeferredTaxAssetsPropertyPlantAndEquipment USD 1.370000e+08
DeferredTaxAssetsTaxDeferredExpenseCompensation... USD 7.490000e+08
DeferredTaxAssetsTaxDeferredExpenseReservesAndA... USD 5.389000e+09
DeferredTaxAssetsUnrealizedLossesOnAvailablefor... USD 0.000000e+00
DerivativeAssetsReductionforMasterNettingArrang... USD 2.700000e+09
IncreaseDecreaseInOtherOperatingAssets USD -8.730000e+08
NoncurrentAssets USD 3.737800e+10
OtherAssetsCurrent USD 1.235200e+10
OtherAssetsNoncurrent USD 3.297800e+10
</pre></div>
</div>
</div>
<div class="section" id="form-liability-sheet-self">
<h3><em>Form.liability_sheet(self)</em><a class="headerlink" href="#form-liability-sheet-self" title="Permalink to this headline">¶</a></h3>
<p>Filters the form to generate a liability sheet. Wrapper around <code class="docutils literal notranslate"><span class="pre">form.filter("Liability|Liabilities")</span></code>.</p>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>pandas.DataFrame</strong></p>
<ul>
<li><p>a pandas dataframe with just values pertaining to liabilities</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form = instance.query10Q("AAPL", (2019, "Q2"))
>>> form.liability_sheet()
fy 2019
fp Q2
tag uom
ContractWithCustomerLiability USD 8.200000e+09
ContractWithCustomerLiabilityCurrent USD 5.532000e+09
ContractWithCustomerLiabilityRevenueRecognized USD 1.900000e+09
DerivativeLiabilitiesReductionforMasterNettingA... USD 1.700000e+09
IncreaseDecreaseInContractWithCustomerLiability USD -5.400000e+08
IncreaseDecreaseInOtherOperatingLiabilities USD -3.273000e+09
Liabilities USD 2.361380e+11
LiabilitiesAndStockholdersEquity USD 3.419980e+11
LiabilitiesCurrent USD 9.377200e+10
LiabilitiesNoncurrent USD 1.423660e+11
OtherAccruedLiabilitiesNoncurrent USD 2.117900e+10
OtherLiabilitiesCurrent USD 3.536800e+10
OtherLiabilitiesNoncurrent USD 5.216500e+10
</pre></div>
</div>
</div>
<div class="section" id="form-debt-sheet-self">
<h3><em>Form.debt_sheet(self)</em><a class="headerlink" href="#form-debt-sheet-self" title="Permalink to this headline">¶</a></h3>
<p>Filters the form to generate a debt sheet. Wrapper around <code class="docutils literal notranslate"><span class="pre">form.filter("Debt|Debts")</span></code>.</p>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>pandas.DataFrame</strong></p>
<ul>
<li><p>a pandas dataframe with just values pertaining to debts</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form = instance.query10Q("AAPL", 2019)
>>> form.debt_sheet()
fy 2019
fp Q1 Q2 Q3
tag uom
AvailableForSaleDebtSecuritiesAccumulatedGrossU... USD 9.400000e+07 3.850000e+08 8.920000e+08
AvailableForSaleDebtSecuritiesAccumulatedGrossU... USD 3.871000e+09 1.532000e+09 4.610000e+08
AvailableForSaleDebtSecuritiesAmortizedCostBasis USD 2.488120e+11 2.265580e+11 2.101790e+11
AvailableForSaleSecuritiesDebtSecurities USD 2.450350e+11 2.254110e+11 2.106100e+11
...
ProceedsFromShortTermDebtMaturingInMoreThanThre... USD 2.166000e+09 1.023500e+10 1.297700e+10
RepaymentsOfLongTermDebt USD NaN 2.500000e+09 5.500000e+09
RepaymentsOfShortTermDebtMaturingInMoreThanThre... USD 4.171000e+09 7.787000e+09 1.128300e+10
ShortTermDebtWeightedAverageInterestRate pure 2.390000e-02 2.560000e-02 2.490000e-02
</pre></div>
</div>
</div>
<div class="section" id="form-to-csv-self-path-or-buf">
<h3><em>Form.to_csv(self, path_or_buf, …)</em><a class="headerlink" href="#form-to-csv-self-path-or-buf" title="Permalink to this headline">¶</a></h3>
<p>Saves the form as a csv file. Wrapper around <a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html">pandas.DataFrame.to_csv</a>;
follow that link for the full documentation.</p>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form = instance.query10Q("aapl", 2018)
>>> form.to_csv("Apple_2018_10Q")
</pre></div>
</div>
</div>
</div>
<div class="section" id="form10k-functions">
<h2>Form10K Functions<a class="headerlink" href="#form10k-functions" title="Permalink to this headline">¶</a></h2>
<p><strong>Form10K</strong> represents a SEC form 10-K and is a subclass of <strong>Form</strong>,
thus inheriting all of the functions included in the <strong>Form</strong> class.</p>
<div class="section" id="form10k-calc-roe-self-as-list-false">
<h3><em>Form10K.calc_ROE(self, as_list=False)</em><a class="headerlink" href="#form10k-calc-roe-self-as-list-false" title="Permalink to this headline">¶</a></h3>
<p>Calculates return on equity (ROE) ratio. ROE = (net income) / (total stockholders equity).</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>as_list : boolean</strong></p>
<ul>
<li><p>returns the values as a list if True, otherwise returns values in a dataframe; defaults
to False</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>list or pandas.DataFrame</strong></p>
<ul>
<li><p>a list or pandas dataframe detailing the ROE for every year in the query</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form10K = instance.query10K("aapl", [2017, 2018, 2019])
>>> form10K.calc_ROE()
fy 2017 2018 2019
tag uom
ROE ratio 0.360702 0.555601 0.610645
</pre></div>
</div>
</div>
<div class="section" id="form10k-calc-currentratio-self-as-list-false">
<h3><em>Form10K.calc_CurrentRatio(self, as_list=False)</em><a class="headerlink" href="#form10k-calc-currentratio-self-as-list-false" title="Permalink to this headline">¶</a></h3>
<p>Calculates the current ratio. CurrentRatio = (current assets) / (current liabilities)</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>as_list : boolean</strong></p>
<ul>
<li><p>returns the values as a list if True, otherwise returns values in a dataframe; defaults
to False</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>list or pandas.DataFrame</strong></p>
<ul>
<li><p>a list or pandas dataframe detailing the CurrentRatio for every year in the query</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form10K = instance.query10K("aapl", [2017, 2018, 2019])
>>> form10K.calc_CurrentRatio()
fy 2017 2018 2019
tag uom
CurrentRatio ratio 1.276063 1.123843 1.540126
</pre></div>
</div>
</div>
<div class="section" id="form10k-calc-debttoequity-self-as-list-false">
<h3><em>Form10K.calc_DebtToEquity(self, as_list=False)</em><a class="headerlink" href="#form10k-calc-debttoequity-self-as-list-false" title="Permalink to this headline">¶</a></h3>
<p>Calculates the debt to equity ratio. DebtToEquity = (total liabilities) / (total stockholders equity)</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>as_list : boolean</strong></p>
<ul>
<li><p>returns the values as a list if True, otherwise returns values in a dataframe; defaults
to False</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>list or pandas.DataFrame</strong></p>
<ul>
<li><p>a list or pandas dataframe detailing the DebtToEquity for every year in the query</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form10K = instance.query10K("aapl", [2017, 2018, 2019])
>>> form10K.calc_DebtToEquity()
fy 2017 2018 2019
tag uom
DebtToEquity ratio 1.799906 2.413301 2.741004
</pre></div>
</div>
</div>
<div class="section" id="form10k-calc-bookvalue-self-as-list-false">
<h3><em>Form10K.calc_BookValue(self, as_list=False)</em><a class="headerlink" href="#form10k-calc-bookvalue-self-as-list-false" title="Permalink to this headline">¶</a></h3>
<p>Calculates the book value. BookValue = (total assets) - (total liabilities)</p>
<p><strong>Parameters:</strong></p>
<ul class="simple">
<li><p><strong>as_list : boolean</strong></p>
<ul>
<li><p>returns the values as a list if True, otherwise returns values in a dataframe; defaults
to False</p></li>
</ul>
</li>
</ul>
<p><strong>Returns:</strong></p>
<ul class="simple">
<li><p><strong>list or pandas.DataFrame</strong></p>
<ul>
<li><p>a list or pandas dataframe detailing the BookValue for every year in the query</p></li>
</ul>
</li>
</ul>
<p>Example usage:</p>
<div class="highlight-<!-- language: python --> notranslate"><div class="highlight"><pre><span></span>>>> form10K = instance.query10K("aapl", [2017, 2018, 2019])
>>> form10K.calc_BookValue(as_list=True)
[1.340470e+11, 1.071470e+11, 9.048800e+10]
</pre></div>
</div>
</div>
</div>
<div class="section" id="form10q-functions">
<h2>Form10Q Functions<a class="headerlink" href="#form10q-functions" title="Permalink to this headline">¶</a></h2>
<p><strong>Form10K</strong> represents a SEC form 10-Q and is a subclass of <strong>Form</strong>,
thus inheriting all of the functions included in the <strong>Form</strong> class.</p>
<p>Currently, there are no functions specifically for <strong>Form10Q</strong>.</p>
</div>
</div>
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