Explorative data analysis of loan data
In this project for the Udacity Nanodegree Data Analyst, I explored loan data from Prosper, an US-based lending platform. The data set contains 113,937 loans and 84 variables. The objectives of the analysis was to summarize the data to determine (1) the relationship between the various variables of interest and (2) how the interest rates for individuals loans can be predicted with the available data. Using R, examined the data with a wide range of exploratory plots and linear regression analysis to determine the aspects that influence interest rates of consumer loans in the US. The complete report, the data and the R-code can be found in this github repository.