Lesson6.py

import sklearn
from sklearn.utils import shuffle
from sklearn.neighbors import KNeighborsClassifier
import pandas as pd
import numpy as np
from sklearn import preprocessing

data = pd.read_csv("F:/NEW/importent folder/main folder/projects for github/AI and AI in Python/codes and files/car.data")

print(data.head())

le = preprocessing.LabelEncoder()

buying = le.fit_transform(list(data["buying"]))
maint = le.fit_transform(list(data["maint"]))
doors = le.fit_transform(list(data["doors"]))
persons = le.fit_transform(list(data["persons"]))
lug_boot = le.fit_transform(list(data["lug_boot"]))
safety = le.fit_transform(list(data["safety"]))
cls = le.fit_transform(list(data["class"]))

x=list(zip(buying, maint, doors, persons, lug_boot, safety))  #features
y=list(cls)  #labels

x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(x,y,test_size=0.1)

#print(data.columns.tolist())

print(x_train)
#print(x_test)
#print(y_train)
#print(y_test)