import pandas as pd

import numpy as np  # Add this line

from sklearn.cluster import KMeans

import seaborn as sns

import warnings

warnings.filterwarnings("ignore", category=RuntimeWarning)

 

data_full = pd.read_csv('/datasets/cars_label.csv')

 

data = data_full.drop(columns=['brand'])

 

# Обучение модели

model = KMeans(n_clusters=3, random_state=12345)

model.fit(data)

 

# Дополнительный слой для центроидов

centroids = pd.DataFrame(model.cluster_centers_, columns=data.columns)

 

centroids['brand'] = ['0 centroid', '1 centroid', '2 centroid']

 

data_all= pd.concat([data_full, centroids], ignore_index=True)

 

pairgrid = sns.pairplot(data_full, hue='brand', vars=data.columns[:-1], diag_kind='hist')