Medium article 1

5.py

import numpy as np
from sklearn.linear_model import LinearRegression

class predit:
    def bestFitLine(self,data):
        size=np.array([500,650,700,780,900,1100,1150,2000,2200,2500]).reshape(-1,1)
        price=np.array([1000,1500,1600,1770,2200,3000,3500,4400,4600,6000]).reshape(-1,1)

        regressionLine=LinearRegression().fit(size,price)
        pred=regressionLine.predict(size)
        ss=regressionLine.predict(data)

        return(ss) 

newHouseSize= np.array([1000, 1550,450,920,980]).reshape(-1,1)
Object= predit()
price= Object.bestFitLine(newHouseSize)
print ("Price of {} sq feet house is {}".format(newHouseSize, price ))