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

dataset = pd.read_csv('DATA/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=1)

lr = LinearRegression()
lr.fit(x_train, y_train)


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