controlling for pessimism and optimism

optipessibias.py

pessimist = [2, 2, 3, 2]                                                                                              
optimist = [4, 4, 5, 4]                                                                                               

def min_max(scores):                                                                                                  
    return list(map(lambda x : (x-min(scores))/(max(scores)-min(scores)), scores))                                    

print(min_max(pessimist)) # [0, 0, 1, 0]                                                                              
print(min_max(optimist))  # [0, 0, 1, 0]                                                                              

def div_avg(scores):                                                                                                  
    avg = float(sum(scores)/len(scores))                                                                              
    return list(map(lambda x : x / avg, scores))                                                                      

print(div_avg(pessimist)) # [0.88, 0.88, 1.33, 0.88]                                                                  
print(div_avg(optimist))  # [0.94, 0.94, 1.17, 0.94]