finagg.sec package

Subpackages

Submodules

finagg.sec.api module

An implementation of the Securities and Exchange Commission’s (SEC) EDGAR API.

The SEC EDGAR API provides methods for retrieving XBRL data (e.g., earnings per share) from financial statements and SEC filing submission histories (e.g., 10-Q/10-K forms). The SEC EDGAR API is one of the few APIs that provides historical and current company financial data for free.

An SEC EDGAR API user agent declaration is required to use this API. The user agent should be of format FIRST_NAME LAST_NAME E_MAIL. You can pass your user agent directly to the implemented API getters, or you can set the SEC_API_USER_AGENT environment variable to have the user agent be passed to the implemented API getters for you.

Alternatively, running finagg sec install (or the broader finagg install) will prompt you to enter an SEC EDGAR API user agent and will automatically store it in an .env file in your current working directory. The environment variables set in that .env file will be loaded into your shell upon using finagg (whether that be through the Python interface or through the CLI tools).

See the official SEC EDGAR API docs for more info on the SEC API.

class finagg.sec.api.Concept[source]

Bases: TypedDict

A collection of XBRL tag (data field), SEC EDGAR taxonomy that tag is in, and units for that tag.

tag: str

Valid tag within the given taxonomy.

taxonomy: str

Valid SEC EDGAR taxonomy. See https://www.sec.gov/info/edgar/edgartaxonomies.shtml for taxonomies.

units: str

Currency the concept is in.

class finagg.sec.api.Frame[source]

Bases: dict

A frame is just a Concept with a flag indicating if it supports “instantaneous” frame data.

instant: bool

Whether to retrieve “instant” calendrical results.

tag: str
taxonomy: str
units: str
class finagg.sec.api.SubmissionsResult[source]

Bases: TypedDict

metadata: dict[str, Any]

Company metadata.

filings: DataFrame

Most recent company filings.

class finagg.sec.api.API[source]

Bases: ABC

Abstract SEC EDGAR API.

url: ClassVar[str]

Request API URL.

abstract classmethod get(*args: Any, **kwargs: Any) → DataFrame | SubmissionsResult[source]

Main API getter method.

class finagg.sec.api.CompanyConcept[source]

Bases: API

Get all XBRL disclosures for a single company and concept (a taxonomy and tag) in a single dataframe.

The module variable finagg.sec.api.company_concept is an instance of this API implementation and is the most popular interface for querying this API.

See also

finagg.sec.api.popular_concepts: For a list of popular company

concepts that can be used with this method. The concepts described within this member are the most widely available concepts for SEC filers.

url: ClassVar[str] = 'https://data.sec.gov/api/xbrl/companyconcept/CIK{cik}/{taxonomy}/{tag}.json'

Request API URL.

classmethod get(tag: str, /, *, cik: None | str = None, ticker: None | str = None, taxonomy: str = 'us-gaap', units: str = 'USD', cache: bool = True, user_agent: None | str = None) → DataFrame[source]

Return all XBRL disclosures for a single company (CIK) and concept (a taxonomy and tag) in a single dataframe.

Parameters:

  • tag – Valid tag within the given taxonomy.

  • cik – Company SEC CIK. Mutually exclusive with ticker.

  • ticker – Company ticker. Mutually exclusive with cik.

  • taxonomy – Valid SEC EDGAR taxonomy. See https://www.sec.gov/info/edgar/edgartaxonomies.shtml for taxonomies.

  • units – Currency to view results in.

  • cache – Whether to cache the response from the API.

  • user_agent – Self-declared bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

Dataframe with normalized column names.

Raises:

ValueError – If both a cik and ticker are provided or neither are provided.

Examples

>>> finagg.sec.api.company_concept.get(
...     "EarningsPerShareBasic",
...     ticker="AAPL",
...     taxonomy="us-gaap",
...     units="USD/shares",
... ).head(5)  
        start         end  value                  accn    fy  fp ...
0  2006-10-01  2007-09-29   4.04  0001193125-09-214859  2009  FY ...
1  2006-10-01  2007-09-29   4.04  0001193125-10-012091  2009  FY ...
2  2007-09-30  2008-06-28   4.20  0001193125-09-153165  2009  Q3 ...
3  2008-03-30  2008-06-28   1.21  0001193125-09-153165  2009  Q3 ...
4  2007-09-30  2008-09-27   5.48  0001193125-09-214859  2009  FY ...
classmethod get_multiple_original(concepts: list[finagg.sec.api.Concept], *, cik: None | str = None, ticker: None | str = None, form: None | str = None, start: None | str = None, end: None | str = None, cache: bool = True, user_agent: None | str = None) → DataFrame[source]

Return original (not amended) XBRL disclosures for a single company using a set of company concepts.

Parameters:

  • concepts – Company concepts to retrieve.

  • cik – Company SEC CIK. Mutually exclusive with ticker.

  • ticker – Company ticker. Mutually exclusive with cik.

  • form – SEC filing form type to include. "10-Q" is for quarterly filing forms and "10-K" is for annual filing forms. Ignored if left None.

  • start – The start date of the observation period. Defaults to the first recorded date.

  • end – The end date of the observation period. Defaults to the last recorded date.

  • cache – Whether to cache the response from the API.

  • user_agent – Self-declared bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

Pivoted dataframe with a tag per column.

Examples

>>> finagg.sec.api.company_concept.get_multiple_original(
...     finagg.sec.api.popular_concepts,
...     ticker="AAPL",
... ).head(5)  
    fy  fp     tag         end         value  ...
0  2009  Q3  Assets  2009-06-27  4.814000e+10 ...
1  2010  Q1  Assets  2009-12-26  5.392600e+10 ...
2  2010  Q2  Assets  2010-03-27  5.705700e+10 ...
3  2010  Q3  Assets  2010-06-26  6.472500e+10 ...
4  2011  Q1  Assets  2010-12-25  8.674200e+10 ...
class finagg.sec.api.CompanyFacts[source]

Bases: API

Get all XBRL disclosures for a single company.

The module variable finagg.sec.api.company_facts is an instance of this API implementation and is the most popular interface for querying this API.

url: ClassVar[str] = 'https://data.sec.gov/api/xbrl/companyfacts/CIK{cik}.json'

Request API URL.

classmethod download_zip(*, chunk_size: int = 1000000, user_agent: None | str = None) → ZipFile[source]

Download all XBRL disclosures for all companies in a zip file.

A progress bar displays the download progress as the download could take a long time because the zip file is more than 1GB. The zip file is updated by the SEC at approximately 3am ET nightly.

Parameters:

  • chunk_size – Chunk size to stream and write the zip file with.

  • user_agent – Self-declared bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

A zip file object representing the downloaded zip file.

classmethod get(*, cik: None | str = None, ticker: None | str = None, cache: bool = True, user_agent: None | str = None) → DataFrame[source]

Return all XBRL disclosures for a single company (CIK).

Parameters:

  • cik – Company SEC CIK. Mutually exclusive with ticker.

  • ticker – Company ticker. Mutually exclusive with cik.

  • cache – Whether to cache the response from the API.

  • user_agent – Self-declared bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

Dataframe with normalized column names.

Raises:

ValueError – If both a cik and ticker are provided or neither are provided.

Examples

>>> finagg.sec.api.company_facts.get(ticker="AAPL").head(5)  
          end       value                  accn    fy  fp    form ...
0  2009-06-27  8.9582e+08  0001193125-09-153165  2009  Q3    10-Q ...
1  2009-10-16  9.0068e+08  0001193125-09-214859  2009  FY    10-K ...
2  2009-10-16  9.0068e+08  0001193125-10-012091  2009  FY  10-K/A ...
3  2010-01-15  9.0679e+08  0001193125-10-012085  2010  Q1    10-Q ...
4  2010-04-09  9.0994e+08  0001193125-10-088957  2010  Q2    10-Q ...
class finagg.sec.api.Exchanges[source]

Bases: API

SEC-registered ticker info with exchange data.

This API implementation is very similar to Tickers. It returns all the same data in addition to the exchanges that each company is on.

The module variable finagg.sec.api.exchanges is an instance of this API implementation and is the most popular interface for querying this API.

url: ClassVar[str] = 'https://www.sec.gov/files/company_tickers_exchange.json'

Request API URL.

classmethod get(*, cache: bool = True, user_agent: None | str = None) → DataFrame[source]

Get a dataframe containing all SEC-registered ticker info.

Parameters:

  • cache – Whether to cache the response from the API.

  • user_agent – Self-declared SEC bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

A dataframe containing company names, their SEC CIKs, and their ticker symbols.

Examples

>>> finagg.sec.api.exchanges.get().head(5)  
       cik            name ticker exchange
0   320193      Apple Inc.   AAPL   Nasdaq
1   789019  MICROSOFT CORP   MSFT   Nasdaq
2  1652044   Alphabet Inc.  GOOGL   Nasdaq
3  1018724  AMAZON COM INC   AMZN   Nasdaq
4  1045810     NVIDIA CORP   NVDA   Nasdaq
class finagg.sec.api.Frames[source]

Bases: API

Get all company filings for one particular fact that most closely matches the requested calendrical period.

The module variable finagg.sec.api.frames is an instance of this API implementation and is the most popular interface for querying this API.

See also

popular_frames: For a list of popular company frames

that can be used with this method. The frames described within this member are the most widely available frames for SEC filers.

url: ClassVar[str] = 'https://data.sec.gov/api/xbrl/frames/{taxonomy}/{tag}/{units}/CY{year}{quarter}.json'

Request API URL.

classmethod get(tag: str, year: int | str, /, quarter: None | int | str = None, *, instant: bool = True, taxonomy: str = 'us-gaap', units: str = 'USD', cache: bool = True, user_agent: None | str = None) → DataFrame[source]

Get one fact for each reporting entity that most closely fits the calendrical period requested.

Parameters:

  • tag – Valid tag within the given taxonomy.

  • year – Year to retrieve.

  • quarter – Quarter to retrieve data for. Most data is only provided at a quarterly rate, so this should be provided for most cases.

  • instant – Whether to get instantaneous data for the frame (data that most closely matches a frame’s year and quarter without a time buffer). This flag should be enabled for most cases. See popular_frames for which tags should be instant.

  • taxonomy – Valid SEC EDGAR taxonomy. See https://www.sec.gov/info/edgar/edgartaxonomies for taxonomies.

  • units – Units to view results in.

  • cache – Whether to cache the response from the API.

  • user_agent – Self-declared bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

Dataframe with slightly improved column names.

Examples

>>> finagg.sec.api.frames.get(
...     "EarningsPerShareBasic",
...     2020,
...     quarter=3,
...     instant=False,
...     taxonomy="us-gaap",
...     units="USD-per-shares",
... ).head(5)  
                   accn   cik                          entity    loc ...
0  0001104659-21-118843  1750                       AAR CORP.  US-IL ...
1  0001104659-21-133629  1800             ABBOTT LABORATORIES  US-IL ...
2  0001264931-20-000235  1961                     WORLDS INC.  US-MA ...
3  0001564590-21-055818  2098                ACME UNITED CORP  US-CT ...
4  0000002178-22-000033  2178  ADAMS RESOURCES & ENERGY, INC.  US-TX ...
class finagg.sec.api.Submissions[source]

Bases: API

Get a company’s metadata and all its recent SEC filings.

Not all the metadata typically found with the submissions API is supported by this API. Only common company metadata (e.g., company name, industry code, fiscal year end date, etc.) is returned by this implementation.

The module variable finagg.sec.api.submissions is an instance of this API implementation and is the most popular interface for querying this API.

url: ClassVar[str] = 'https://data.sec.gov/submissions/CIK{cik}.json'

Request API URL.

classmethod download_zip(*, chunk_size: int = 1000000, user_agent: None | str = None) → ZipFile[source]

Download all SEC filings for all companies in a zip file.

A progress bar displays the download progress as the download could take a long time because the zip file is more than 1GB. The zip file is updated by the SEC at approximately 3am ET nightly.

Parameters:

  • chunk_size – Chunk size to stream and write the zip file with.

  • user_agent – Self-declared bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

A zip file object representing the downloaded zip file.

classmethod get(*, cik: None | str = None, ticker: None | str = None, cache: bool = True, user_agent: None | str = None) → SubmissionsResult[source]

Return a company’s metadata and all its recent SEC filings.

Parameters:

  • cik – Company SEC CIK. Mutually exclusive with ticker.

  • ticker – Company ticker. Mutually exclusive with cik.

  • cache – Whether to cache the response from the API.

  • user_agent – Self-declared SEC bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

Company metadata and a dataframe with recent SEC filings.

Raises:

ValueError – If both a cik and ticker are provided or neither are provided.

Examples

>>> out = finagg.sec.api.submissions.get(ticker="AAPL")
>>> out["metadata"]  
{'cik': '0000320193', 'entityType': 'operating', 'sic': '3571', ...}
class finagg.sec.api.Tickers[source]

Bases: API

SEC-registered ticker info.

This is a broader method in comparison to get_ticker_set(). get_ticker_set() will get all the tickers that have popular fundamentals data available through the SEC EDGAR API for the previous year, while this method will get all tickers and CIKs that have ever had data available via the SEC EDGAR API.

The module variable finagg.sec.api.tickers is an instance of this API implementation and is the most popular interface for querying this API.

url: ClassVar[str] = 'https://www.sec.gov/files/company_tickers.json'

Request API URL.

classmethod get(*, cache: bool = True, user_agent: None | str = None) → DataFrame[source]

Get a dataframe containing all SEC-registered ticker info.

Parameters:

  • cache – Whether to cache the response from the API.

  • user_agent – Self-declared SEC bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

A dataframe containing company names, their SEC CIKs, and their ticker symbols.

Examples

>>> finagg.sec.api.tickers.get().head(5)  
       cik ticker                   title
0   320193   AAPL              Apple Inc.
1   789019   MSFT          MICROSOFT CORP
2  1652044  GOOGL           Alphabet Inc.
3  1018724   AMZN          AMAZON COM INC
4  1067983  BRK-B  BERKSHIRE HATHAWAY INC
finagg.sec.api.company_concept

The most popular way for accessing the CompanyConcept API implementation.

finagg.sec.api.company_facts

The most popular way for accessing the CompanyFacts API implementation.

finagg.sec.api.exchanges

The most popular way for accessing the Exchanges API implementation.

finagg.sec.api.frames

The most popular way for accessing the Frames API implementation.

finagg.sec.api.submissions

The most popular way for accessing the Submissions API implementation.

finagg.sec.api.tickers

The most popular way for accessing the Tickers API implementation.

finagg.sec.api.popular_frames: list[finagg.sec.api.Frame]

Company frames that have high availability and are relatively popular for fundamental analysis. Includes things like earnings per share, current assets, etc.. Frames are in valid format for usage with the Frames API implementation.

finagg.sec.api.popular_concepts: list[finagg.sec.api.Concept]

Company concepts that have high availability and are relatively popular for fundamental analysis. Includes things like earnings per share, current assets, etc.. Concepts contain all the parameters required for usage with the CompanyConcept API implementation.

finagg.sec.api.compute_financial_ratios(df: DataFrame, /) → DataFrame[source]

Compute financial ratios in-place for a dataframe using XBRL financial tags.

Parameters:

df – Dataframe with common XBRL financial tags (e.g., “Assets”, “Liabilities”, etc.).

Returns:

df but with additional columns that’re normalized financial ratios.

finagg.sec.api.filter_original_filings(df: DataFrame, /, *, form: None | str = None, units: None | str = None) → DataFrame[source]

Get all original filing rows as determined by the filing date and tag for a period.

Parameters:

  • df – Dataframe without mixed original and amendment rows.

  • form – Only keep rows with form type form. Most popular choices include "10-K" for annual and "10-Q" for quarterly. This parameter is ignored if left None.

  • units – Only keep rows with units units if not None.

Returns:

Dataframe with rows that only correspond to original filings.

Examples

Only get a company’s original quarterly earnings-per-share filings.

>>> df = finagg.sec.api.company_concept.get(
...     "EarningsPerShareBasic",
...     ticker="AAPL",
...     taxonomy="us-gaap",
...     units="USD/shares",
... )
>>> finagg.sec.api.filter_original_filings(
...     df,
...     form="10-Q",
...     units="USD/shares"
... ).head(5)  
     fy  fp  ...
0  2009  Q3  ...
1  2010  Q1  ...
2  2010  Q2  ...
3  2010  Q3  ...
4  2011  Q1  ...
finagg.sec.api.get_cik(ticker: str, /, *, user_agent: None | str = None) → str[source]

Return a company’s SEC CIK from its ticker.

Parameters:

  • ticker – A company’s ticker symbol.

  • user_agent – Self-declared SEC bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

The company’s corresponding SEC CIK.

Examples

Get Apple’s SEC CIK from its ticker.

>>> finagg.sec.api.get_cik("AAPL") == "0000320193"
True
finagg.sec.api.get_ticker(cik: str, /, *, user_agent: None | str = None) → str[source]

Return a company’s ticker from its SEC CIK.

Parameters:

  • cik – A company’s 10-character SEC CIK.

  • user_agent – Self-declared SEC bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

The company’s corresponding ticker.

Examples

Get Apple’s ticker from its SEC CIK.

>>> finagg.sec.api.get_ticker("0000320193") == "AAPL"
True
finagg.sec.api.get_ticker_set(*, user_agent: None | str = None) → set[str][source]

Get the set of tickers that published data for popular concepts during any of the quarters for the previous year.

This effectively gets the set of tickers whose data is at least somewhat available through the SEC EDGAR API.

Parameters:

user_agent – Self-declared SEC bot header. Defaults to the value found in the SEC_API_USER_AGENT environment variable.

Returns:

Set of tickers whose data is at least somewhat available through the SEC EDGAR API.

Examples

>>> tickers = finagg.sec.api.get_ticker_set()
>>> "AAPL" in tickers
True
>>> "MSFT" in tickers
True
>>> "GOOG" in tickers
True
finagg.sec.api.group_and_pivot_filings(df: DataFrame, /, *, form: None | str = None) → DataFrame[source]

Helper for grouping filings into a pivoted dataframe such that each tag has its own column.

Tags are grouped according to fiscal year and fiscal period. The newest filing date is used when tags have different filing dates for the same fiscal year and fiscal period. Tags are forward-filled to fill gaps in filings.

Parameters:

  • df – “Melted” dataframe where each filing is a row.

  • form – Type of form to group. "10-K" sets the index to the fiscal year and filing date whereas "10-Q" sets the index to the fiscal year, fiscal period, and filing date. If not provided, the form type is chosen by inspecting the first element of the "form" column.

Returns:

A pivoted dataframe where each column is a tag.

Examples

Get all XBRL filings from a company, unintelligently select the first unique filings for each XBRL tag, and then group all filings into a pivoted table.

>>> df = finagg.sec.api.company_facts.get(ticker="AAPL")
>>> df = finagg.sec.api.filter_original_filings(df, form="10-K")
>>> finagg.sec.api.group_and_pivot_filings(df, form="10-K")  
                 AccountsPayableCurrent  AccountsReceivableNetCurrent ...
fy   filed                                                            ...
2009 2009-10-27            5.520000e+09                  2.422000e+09 ...
2010 2010-10-27            5.601000e+09                  3.361000e+09 ...
2011 2011-10-26            1.201500e+10                  5.510000e+09 ...
2012 2012-10-31            1.463200e+10                  5.369000e+09 ...
2013 2013-10-30            2.117500e+10                  1.093000e+10 ...

finagg.sec.sql module

SEC SQLAlchemy interfaces.

finagg.sec.sql.metadata

The metadata associated with all SQL tables defined in this module.

finagg.sec.sql.submissions

SQL table for storing raw data as managed by finagg.sec.feat.submissions (an alias for finagg.sec.feat.Submissions).

finagg.sec.sql.tags

SQL table for storing raw data as managed by finagg.sec.feat.tags (an alias for finagg.sec.feat.Tags).

finagg.sec.sql.annual

SQL table for storing refined data as managed by finagg.sec.feat.annual (an alias for finagg.sec.feat.Annual).

finagg.sec.sql.normalized_annual

SQL table for storing refined data as managed by finagg.sec.feat.Annual.normalized (an alias for finagg.sec.feat.NormalizedAnnual).

finagg.sec.sql.quarterly

SQL table for storing refined data as managed by finagg.sec.feat.quarterly (an alias for finagg.sec.feat.Quarterly).

finagg.sec.sql.normalized_quarterly

SQL table for storing refined data as managed by finagg.sec.feat.Quarterly.normalized (an alias for finagg.sec.feat.NormalizedQuarterly).

finagg.sec.sql.get_cik(ticker: str, /, *, engine: None | Engine = None) → str[source]

Use raw SQL data to find a company’s SEC CIK from its ticker symbol.

This is the preferred method for getting a company’s SEC CIK if raw SQL data is installed. This method is a convenience over finagg.sec.api.get_cik() for repeatedly getting company SEC CIKs without having to query the SEC EDGAR API. Use finagg.sec.api.get_cik() if you want to get a company’s ticker symbol without installing or accessing locally installed raw SQL data.

Parameters:

  • ticker – A company’s ticker symbol.

  • engine – Feature store database engine. Defaults to the engine at finagg.backend.engine.

Returns:

The company’s corresponding SEC CIK.

Examples

Get Apple’s SEC CIK from its ticker.

>>> finagg.sec.sql.get_cik("AAPL") == "0000320193"
True
finagg.sec.sql.get_metadata(*, cik: None | str = None, ticker: None | str = None, engine: None | Engine = None) → dict[str, Any][source]

Return a company’s metadata (its SEC CIK, ticker, name, and industry code) from its SEC CIK or its ticker symbol.

A convenient method for getting a company’s metadata using raw SQL data. This method is a convenience over finagg.sec.api.submissions for repeatedly getting company metadata without having to query the SEC EDGAR API. Use finagg.sec.api.submissions if you want to get a company’s metadata without installing or accessing locally installed raw SQL data.

Parameters:

  • cik – Company SEC CIK. Mutually exclusive with ticker.

  • ticker – Company ticker. Mutually exclusive with cik.

  • engine – Feature store database engine. Defaults to the engine at finagg.backend.engine.

Returns:

A company’s metadata as a dictionary.

Examples

>>> finagg.sec.sql.get_metadata(ticker="MSFT")
{'cik': '0000789019', 'ticker': 'MSFT', 'name': 'microsoft corp', 'sic': '7372'}
finagg.sec.sql.get_ticker(cik: str, /, *, engine: None | Engine = None) → str[source]

Use raw SQL data to find a company’s ticker from its SEC CIK.

This is the preferred method for getting a company’s ticker if raw SQL data is installed. This method is a convenience over finagg.sec.api.get_ticker() for repeatedly getting company tickers without having to query the SEC EDGAR API. Use finagg.sec.api.get_ticker() if you want to get a company’s ticker symbol without installing or accessing locally installed raw SQL data.

Parameters:

  • cik – A company’s SEC CIK.

  • engine – Feature store database engine. Defaults to the engine at finagg.backend.engine.

Returns:

The company’s corresponding ticker symbol.

Examples

Get Apple’s ticker from its SEC CIK.

>>> finagg.sec.sql.get_ticker("0000320193") == "AAPL"
True
finagg.sec.sql.get_tickers_in_industry(*, ticker: None | str = None, code: None | str = None, level: Literal[2, 3, 4] = 2, engine: None | Engine = None) → set[str][source]

Get a set of tickers that all share the same industry using raw SQL data.

This method is convenient for finding tickers within the same industry so they can be compared. A related and common pattern is to use finagg.sec.feat.Quarterly.normalized to get industry-normalized features for a particular company. Similar to other methods in this submodule, this will only return tickers that have raw SQL data associated with them.

Parameters:

  • ticker – Company ticker. Lookup the industry associated with this company. Mutually exclusive with code.

  • code – Industry SIC code to use for industry lookup. Mutually exclusive with ticker.

  • level –

    Industry level to find tickers within. The industry used according to ticker or code is subsampled according to this value. Options include:

    • 2 = major group (e.g., furniture and fixtures)

    • 3 = industry group (e.g., office furnitures)

    • 4 = industry (e.g., wood office furniture)

  • engine – Feature store database engine. Defaults to the engine at finagg.backend.engine.

Returns:

A set of tickers that all share the same industry as denoted by another ticker (using the ticker arg) or an industry SIC code (using the code arg).

Examples

>>> "ETSY" in finagg.sec.sql.get_tickers_in_industry(ticker="MSFT")
True

Module contents

Top-level SEC interface.