# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.preprocessing import LabelEncoder,OneHotEncoder
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

#dataset
dataset = pd.read_csv('50_Startups.csv')

X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, -1].values

labelencoder = LabelEncoder()
X[:, 3] = labelencoder.fit_transform(X[:, 3])

onehotencoder = OneHotEncoder(categorical_features = [3])
X = onehotencoder.fit_transform(X).toarray()

X = X[:, 1:]

X_train,X_test, y_train, y_test = train_test_split(X,y, test_size = 0.2, random_state = 0)

regressor = LinearRegression()
regressor = regressor.fit(X_train,y_train)

y_pred = regressor.predict(X_test)

