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import pandas as pd
import numpy as np
#%matplotlib inline
import matplotlib.pyplot as plt
from IPython.display import display, HTML
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from operator import attrgetter
from matplotlib.patches import Ellipse
from math import atan2,degrees
import numpy.random as rnd


    

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points = pd.read_csv('Clustering.csv',sep=',')


    

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class CenterValue:
    def __init__ (self,p,val):
        self.value=val
        self.point=p


    

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def Distance(p1,p2indx):
    p1 = np.array(p1)
    P2 = np.array((points.X[p2indx],points.Y[p2indx]))
    return np.linalg.norm(p1-p2)


    

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def K_mean(centerpoints):
    centers={}
    for i in centerpoints:
        centers[i]=[]
    for i in range(len(points.index)):
        values=[]


    

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def GetPointsList(Indexs):
    lst=[]
    for i in Indexs:
        lst.append((points.X[i],points.Y[i]))
    return lst


    

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K_mean(GetPointsList(range(4)))


    

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5.0

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