Python code for basic linear regression

Question

I have a housing Data set and I would like to predict the price of a house using linear regression using python. Could i please get the code? Thanks

Answer 1

Hi @Dipti, you could try something like this:

import matplotlib 
matplotlib.use('GTKAgg') 

import matplotlib.pyplot as plt 
import numpy as np 
from sklearn import datasets, linear_model 
import pandas as pd 

# Load CSV and columns 
df = pd.read_csv("Housing.csv") 

Y = df['price'] 
X = df['lotsize'] 

X=X.reshape(len(X),1) 
Y=Y.reshape(len(Y),1) 

# Split the data into training/testing sets 
X_train = X[:-250] 
X_test = X[-250:] 

# Split the targets into training/testing sets 
Y_train = Y[:-250] 
Y_test = Y[-250:] 

# Plot outputs 
plt.scatter(X_test, Y_test, color='black') 
plt.title('Test Data') 
plt.xlabel('Size') 
plt.ylabel('Price') 
plt.xticks(()) 
plt.yticks(()) 

# Create linear regression object 
regr = linear_model.LinearRegression() 

# Train the model using the training sets 
regr.fit(X_train, Y_train) 

# Plot outputs 
plt.plot(X_test, regr.predict(X_test), color='red',linewidth=3) 
plt.show() 

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