def mean_absolute_bias(LeadDay,df,model,observed):
    """
    Args:
        LeadDay: specifically applies to forecast models with lead times
            if no lead day is available input None
            LeadDay is desired Lead day (int)
        df: data frame where Observed and Model data is found
        model & observed : column name (string)
 
    Return:
        mean bias
    Function:
         subtract model values from observed,
        add all errors and divide by number of 
        values
    """
    count =0
    avgdiff=0
    
    if LeadDay is None:
         for a, j in zip(df[observed], df[model]):
            avgdiff += abs((a)-(j))
            count+=1
    else:        
         for a, j in zip(df[LeadDay][observed], df[LeadDay][model]):
            avgdiff += abs((a)-(j))
            count+=1
            
    return avgdiff/count