jmsword

import pandas as pd
import statsmodels.api as sm
import numpy as np

#read in clean loan data
df = pd.read_csv('loansData_clean.csv')

#create column to highlight interest rates below 12%
df['IR_TF'] = df['Interest.Rate'] > .12

jmsword

import pandas as pd
import statsmodels.api as sm
import numpy as np

#read in clean loan data
df = pd.read_csv('loansData_clean.csv')

#create column to highlight interest rates below 12%
df['IR_TF'] = df['Interest.Rate'] > .12

jmsword

import pandas as pd
import statsmodels.api as sm

df = pd.read_csv('loansData_clean.csv')

df['IR_TF'] = df['Interest.Rate'] > .12

df['IR_TF'] = df['IR_TF'].map(lambda x: 1 if x == True else 0)

df['Statsmodel.Intercept'] = df['Interest.Rate'].map(lambda x: 1)

jmsword

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import statsmodels.api as sm

loansData = pd.read_csv('https://github.com/Thinkful-Ed/curric-data-001-data-sets/raw/master/loans/loansData.csv')

#Remove '%' from 'Interest.Rate' column and contert to number
loansData['Interest.Rate']=loansData['Interest.Rate'].map(lambda x: round(float(x.rstrip('%')) / 100, 4))
#Remove 'months' from the 'Loan.Length' column

jmsword

from scipy import stats
import collections
import pandas as pd
import matplotlib.pyplot as plt

loansData = pd.read_csv('https://github.com/Thinkful-Ed/curric-data-001-data-sets/raw/master/loans/loansData.csv')

loansData.dropna(inplace=True)

freq = collections.Counter(loansData['Open.CREDIT.Lines'])

jmsword

import matplotlib.pyplot as plt
import pandas as pd
import scipy.stats as stats

loansData = pd.read_csv('https://github.com/Thinkful-Ed/curric-data-001-data-sets/raw/master/loans/loansData.csv')

loansData.dropna(inplace=True)

loansData.boxplot(column='Amount.Requested')
plt.savefig('Amount Requested Boxplot.png')

jmsword

import numpy as np 
import scipy.stats as stats
import collections
import matplotlib.pyplot as plt


x = [1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 3, 4, 4, 4, 4, 5, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 9, 9]

c = collections.Counter(x)
count_sum = sum(c.values())

jmsword

from sqlalchemy import create_engine
from sqlalchemy import Column, Integer, String, ForeignKey, DateTime
from sqlalchemy.orm import sessionmaker
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base

engine = create_engine('postgresql://ubuntu:thinkful@localhost:5432/tbay')
Session = sessionmaker(bind=engine)
session = Session()
Base = declarative_base()

jmsword

#modeling the bicycle industry

#classes
class bicycle(object):
    
#create the bicycle class so that each bike created has a model name, weight, and cost to produce
    def __init__(self, model, weight, cost):
        self.model = model
        self.weight = weight
        self.cost = cost

jmsword

#modeling the bicycle industry

#create the customer class
class customer(object):
    def __init__(self, name, fund):
        self.name = name
        self.fund = fund

#create the bicycle class so that each bike created has a model name, weight, and cost to produce
class bicycle(object):