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

dataset = pd.read_csv('50_Startups.csv')
x = dataset.iloc[:, :-1].values
y = dataset.iloc[: , -1].values


from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [3])], remainder='passthrough')
x = np.array(ct.fit_transform(x))

from sklearn.model_selection 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
mlr = LinearRegression()
mlr.fit(x_train , y_train)

y_pred = mlr.predict(x_test)
np.set_printoptions(precision=2)
print(np.concatenate((y_pred.reshape(len(y_pred),1), y_test.reshape(len(y_pred),1)), 1))