Simple python ML example

import pandas as pd
import numpy as np
import sklearn
from sklearn import linear_model

df = pd.read_csv('MatchTimelinesFirst15.csv', delimiter=',')


predict = "blue_win"

df = df.drop('Unnamed: 0', axis=1)
df = df.drop('redDragonKills', axis=1)
df = df.drop('blueDragonKills', axis=1)
# print(df.describe())

x = np.array(df.drop([predict], axis=1))
y = np.array(df[predict])

x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(x, y, test_size=0.2)

#print('{0}, {1}'.format(type(x_train), x_train))

linear = linear_model.LinearRegression()
# trains model
linear.fit(x_train, y_train)

acc = linear.score(x_test, y_test)

print('Acc {0}'.format(acc))