import pandas as pd
import matplotlib.pyplot as plt

loansData = pd.read_csv('loansData.csv')


month = lambda x: x[:-6]
percent = lambda x: float(x[:-1])
fico = lambda x: x[:-4]
amount = lambda x: float(x)

loansData['Interest.Rate'] = map(percent, loansData['Interest.Rate'])
loansData['Loan.Length'] = map(month, loansData['Loan.Length'])
loansData['FICO.Score'] = map(fico, loansData['FICO.Range'])
loansData['Amount.Requested'] = map(amount, loansData['Amount.Requested'])

#is there is a better way of doing this? loansData['FICO.Score'] = map(fico, loansData['FICO.Range'].astype(int))


A = loansData['FICO.Score'].tolist()
NewA = []

#for row in A:
 #   NewA.append(int[row])

for row in range(len(A)):
    num = int(A[row])
    NewA.append(num)


loansData['FICO.Score'] = NewA


plt.figure()
p = loansData['FICO.Score'].hist()
plt.show()

print loansData

a = pd.scatter_matrix(loansData, alpha=0.05, figsize=(10,10))

plt.show()