import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.axes3d import Axes3D
import numpy as np
data = np.array( [ [ 5.0 , 5.0, 5.0],
[ 0.0 , 0.0, 0.0],
[ 3.0 , 7.0, 2.0],
[ 4.0 , 4.0, 8.0],
[ 5.0 , 8.0, 9.0],
[ 6.0 , 5.0, 7.0],
[ 7.0 , 9.0, 4.0],
[ 8.0 , 5.0, 1.0],
[ 8.0 , 2.0, 3.0],
[10.0 , 2.0, 5.0] ])
def euclidean_distance(p1, p2):
    d = 0.0
    for i in range(len(p1)):
        a = float(p1[i])
        b = float(p2[i])
        d += np.power((a-b),2)
    d = np.sqrt(d)
    return d
print("\nAll Euclidean Distance from point: ",data[0], "\n")
for point in data:
    distance = euclidean_distance(data[0], point)
    print(distance)
categories = np.array([0,1,1,1,1,2,2,2,2,2])
colormap = np.array(['r', 'g', 'b'])
fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(data[:,0], data[:,1],data[:,2], s=150, c=colormap[categories])
plt.show()