ADP

# -*- coding: utf-8 -*-
"""
Created on Tue May 28 11:53:41 2019

@author: lancernik
"""
#
from sklearn.datasets.samples_generator import make_blobs
from sklearn.cluster import SpectralClustering
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.decomposition import PCA
import pandas as pd
X,y= make_blobs(n_samples=50, centers=5,random_state=0,n_features=15)





X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)

pca = PCA(n_components=7)
principalComponents = pca.fit_transform(X)
principalDf = pd.DataFrame(data = principalComponents
             , columns = ['1', '2','3','4','5','6','7'])


print(pca.explained_variance_ratio_)