Metadata-Version: 2.1
Name: equities
Version: 3.0.2
Summary: equities aims to democratize access to public company financial data.
Home-page: https://github.com/ljc-codes/equities.git
Author: Tiger_Shark
Author-email: ljwcharles@gmail.com
License: UNKNOWN
Description: 
        # 🐋 equities 
        #### access to public company financial data
        
        ## Overview: 
        
            equities allows for easy access to the SEC's XBRL Financial Statement Dataset.
            Data is served to the user in pandas dataframes. equities is powered by polity.
        
        ###### The Dataset: 
        
        https://www.sec.gov/dera/data/financial-statement-data-sets.html
        
        ## Install: 
        
            pip3 install equities
        
        ## TUTORIAL: 
        
        #### Instantiating a Universe
        
        We begin by initializing a universe client.
        
            from equities import Universe
            universe = Universe()
        
        #### Essential Methods 
        
        To get the number of companies in the universe call: 
            len(universe)
        
        "CIK" numbers are the sec's official unique identifier for public companies. To get a full list of the cik numbers call:
        
            universe.ciks()
        
        To get a dictionary mapping "cik" numbers to the names of companies execute:
        
            universe.ciks_to_names()
        
        ## Company Queries: 
        
        #### Requesting Company Json Data
        
        Company data can be accessed in data format by specifying the company's "cik" number.
        
            universe.Company(cik)      # full json data response (metadata and dataframes)
        
        #### Requesting Dataframes of Financial Statements
        
        Full XLBR pandas dataframes of a company's financial statements can be obtained by specifying the company's "cik" number and the "kind" of the statement: 
        
            universe.Statement(cik,"income")      # income statement dataframe
        
            universe.Statement(cik,"balance")     # balance sheet dataframe
        
            universe.Statement(cik,"cash")        # cashflow statement dataframe
        
            
        #### Example 
        
        I really want to demonstrate the beauty of this dataset since this is often difficult when looking
        at thousands of numeric datatables. Let's take a very naive peek by plotting various statements 
        as a kind of stacked timeseries. 
        
        The following is a start to finish example of how one might plot the financial statements 
        of the first five companies in the universe.
        
        Here's how we'd implement that: 
        
            from equities import Universe
            import matplotlib.pyplot as plt 
        
            universe = Universe()
        
            k,f,s = 'bar',(20,10),True
            for cik in universe.ciks()[:5]:
        
                universe.Statement(cik,kind="income").T.plot(
                    kind=k,
                    figsize=f,
                    stacked=s)
        
                universe.Statement(cik,kind="balance").T.plot(
                    kind=k,
                    figsize=f,
                    stacked=s)
        
                universe.Statement(cik,kind="cash").T.plot(
                    kind=k,
                    figsize=f,
                    stacked=s)
        
            plt.show()
        
        ## Donate: 
        
        Consider donating bitcoin 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 scraper parser pandas
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
