import numpy as np
import pandas as pd
import matplotlib.pyplot as plt


dataset=pd.read_csv("50_Startups.csv")
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 4].values

from sklearn.preprocessing import LabelEncoder,OneHotEncoder
labelencoder = LabelEncoder()
X[:, 3] = labelencoder.fit_transform(X[:, 3])
onehotencoder = OneHotEncoder(categorical_features = [3])
X = onehotencoder.fit_transform(X).toarray()

X = X[:, 1:]

from sklearn.cross_validation import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)

from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train, y_train)

 y_pred = regressor.predict(X_train)
 
