this dataset is consist fro some infromation from https://www.prosper.com/ , which includeing (ListingKey','ListingNumber','CreditGrade','ClosedDate','EmploymentStatus', 'IsBorrowerHomeowner','IncomeRange','IncomeVerifiable', (Alpha)','LoanStatus','AvailableBankcardCredit','Recommendations','ProsperScore','PercentFunded', 'TradesOpenedLast6Months') and others .

number of borrower owning home is around 50% of the population borrowers with income range (25k$ to 50K $) is large number of population then 50K$ : 75K$ then +100K $ borrowers with empolyed stautes is large number of population then who have full time . also borrowers with title professionla is hight then computer programe Test relation between two quantattive values correlation factor is very small of colleration and graph used to different method to observe the relation between owning home and income range and liky found that the range of 100k dollar is person who owning home is more studeied the skewness of propser rating and estimated return to test the investment based on prospoer score five number analysis between prospor score and Estimated Return to show median and range >>> relation to assure the affect of recoomandation and prospor score on recommandatio and aslo show realtion between term of loans period by month and loan original amount with respect to monthly loan payment¶ relation between prospor score and recommendation with referance to prospor rating alpha major of with A score this a relation between Borrow annaul per revnue and Stated monthly income with respect to prosper raring show realtion between term of loans period by month and loan original amount with respect to monthly loan payment

my purpose from this insight to check the behaviour of borrowe ( have home or not , employment , ....) and test if follow up the recommendation and website score i will have investment or not