Bankruptcy prediction by using Z-score
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The Altman s Z score is used to predict the possibility of a firm goes 
    to bankruptcy. This score is a weighted average of 5 ratios based 
    on a firm s balance sheet and income statement. For public firms, 
    Altman (1968) offers the following formula. 

     Z=3.3*X1+0.99*X2+0.6*X3+1.2*X4+1.4*X5, 			(1)

    where the definitions of X1,X2,X3,X4 and X5 are given in the following table. 
      Variable	Definition 
      --        -------------
      X1        EBIT/Total Assets
      X2        Net Sales/Total Assets
      X3        Market Value of Equity/Total Liabilities
      X4        Working Capital/Total Assets
      X5        Retained Earnings/Total Assets

    Based on the ranges of z-scores, we could classify public firms 
         into following 4 categories. Eidlenan (1995) finds that the 
         Z score correctly predicted 72% of bankruptcies two years 
         prior to the event.

        Z-score range	Description
        -------------   --------------
          > 3.0          Safe
          2.7 to 2.99    On Alert. 
          1.8 to 2.7     Good chances of going bankrupt within 2 years. 
          < 1.80         Probability of Financial distress is very high 

    References
       Altman, Edward I.,2000,Predicting Financial Distress of Companies, 
           Retrieved on September 4th, 2009 from http://pages.stern.nyu.edu/~ealtman/Zscores.pdf

       Altman, Edward I,1968,Financial Ratios, Discriminant Analysis and the 
           Prediction of Corporate Bankruptcy, Journal of Finance,189 209.
       
       Eidleman, Gregory J.,1995,Z-Scores   A Guide to Failure Prediction, 
           The CPA Journal Online, https://www.easycalculation.com/statistics/altman-z-score.php

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generate a virtual environment
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 Step 1: > mkdir projectA
 Step 2: > cd projectA
 Step 3: > python -m venv env
 Step 4: > env\Scripts\activate    # for Windows
         > source env/bin/activate   # Bash
 Step 5: pip install statsmodels pandas

 env/Scripts/activate.bat //In CMD
 env/Scripts/Activate.ps1 //In Powershe
 deactivate

https://www.freecodecamp.org/news/how-to-setup-virtual-environments-in-python/
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