Python Code - Applied

Python is a powerful tool for accounting research and data analytics. On this webpage, I share some python code to demonstrate how I use Python for accounting research with a focus on the following topics:

• How to get access to XBRL from SEC EDGAR;
  
• How to get data from WRDS;
  
• How to handle data using Pandas and Numpy;
  
• How to visualize data, either static or dynamic.
  

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All code files are stored here. Check anything you’re interested in:

• How to get access to XBRL data from SEC EDGAR using Python.
  
• How to get access to PCAOB AP filings.
  
  • Download AP filings.
    
  • Cleanse AP filings.
    
• How to get access to WRDS using Python.
  
  • Compustat
    • Company.
    • funda (10-K).
    • fundq (10-Q).
    • Segment files.
  • CRSP
    • Monthly files: msf; msi; mse.
    • Daily files: dsf; dsi; dse; dsedelist.
    • CRSP-Compustat Merged (CCM).
    • CRSP-IBES Link.
  • IBES
    • ID files: id; idsum.
    • surpsumu (surprise, unadjusted).
    • det_guidance (Guidance).
  • Audit Analytics
    • Client info (auditcblock)
    • Panel sets: Audit Opinions; SOX404; Sox302; Accelerated filers.
    • Event sets: CAMs; IPOs; Bankruptcy; Data breach; Restatements; Late filings; Auditor changes; Comment letters.
  • BoardEx
    • board chars.
• Financial data for one company: UBER.
• Can we get IPO years from Compustat? Yes we can. Check the distribution.
  
• Yearly distribution of loss firms: More than half are loss firms in 2020.
  
  • Version 1. Using matplotlib after aggregating data method.
    
  • Version 2. Using seaborn and raw data method.
    
• SEC filing distribution provided by SEC EDGAR.
  
• Does the earning kink at zero still exist? Maybe not any more. Check the distribution.
  
• Earnings announcement date distribution using IBES.
  
• Seaborn allows to visualize data with multiple dimensions: scatterplot of firm size, profitability, and auditor size.
  
• Plotly for animated visualization
  
  • Auditors’ client distribution.
    
  • Dynamic scatter plot: ROA & Sales over time.
    
• WRDS processes some BoardEx datasets and provides the processed ones as well as raw ones. Are they reliable? See the figure at the end of this code.