df.score: Application ScoreCard for Credit Risk Model
In prk327/AtConP: Data Preparation

This Function will create a application scorecard from the predicted probability of the logistic regression model. Suppose we have to Build an application scorecard with the good to bad odds of 10 to 1 at a score of 400 doubling every 20 points. So here Odd will be 10, pdo will be 20 and score will be 400.

1 2	df.score(Applicant = NULL, PD = NULL, True_Label = NULL, score = NULL, pdo = NULL, Odd = NULL)

`Applicant`	this the unique applicant id for which we are require to create a score card
`PD`	this is the predicted propability which is generated by using predict() function on logistic model.
`True_Label`	this will the actual label for which prediction is generated either from train or test data sets.
`score`	this is the maximum score that is given to the applicant who is very active in paying the debts owe to him.
`pdo`	this is the point to double the odds
`Odd`	this the good to bad odd