import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
from sklearn.linear_model import LinearRegression

dataset = pd.read_csv('50_Startups.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, -1].values
ct = ColumnTransformer(transformers=[('encoder',OneHotEncoder(),[3])],remainder='passthrough')
X = np.array(ct.fit_transform(X))

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

lr = LinearRegression()
lr.fit(X_train,y_train)
y_predicted = lr.predict(X_test)

np.set_printoptions(precision=2)
print(np.concatenate((y_predicted.reshape(len(y_predicted),1),y_test.reshape(len(y_test),1)),1))