[Data Science] Clustering Wines Project - Pandas Pandas Pandas

Question

Hi guys, I failed in test case 3 while passing the others. Don't know where did I go wrong.. can any master help me? Thank you very much :D
import numpy as np
n = int(input())
X = []
for i in range(n):
X.append([float(x) for x in input().split()])
point_1 = np.array((0.,0.))
point_2 = np.array((2.,2.))
cluster_0 = []
cluster_1 = []
for i in X:
if np.linalg.norm(np.array(tuple(i)) - point_1) <= np.linalg.norm(np.array(tuple(i)) - point_2):
cluster_0.append(np.array(i))
else:
cluster_1.append(np.array(i))
mean_1 = np.mean(cluster_0[:], axis = 0)
mean_2 = np.mean(cluster_1[:], axis = 0)
if np.array(cluster_0).size == 0:
print(None)
else:
print(np.round(mean_1, 2))
if np.array(cluster_1).size == 0:
print(None)
else:
print(np.round(mean_2, 2))

Answer 1

Solved by John Robotane's solution in another discussion thread. Thanks!!
(here's his suggestion: if n1 or n2 is null you will have an error on line 25 or line 26. I suggest you, before calculating the means to first test if those numbers are not null. I suppose that in this test, one of your variables n1 or n2 will be null.)
My final code:
import numpy as np
n = int(input())
X = []
for i in range(n):
X.append([float(x) for x in input().split()])
point_1 = np.array([0.,0.])
point_2 = np.array([2.,2.])
cluster_0 = []
cluster_1 = []
for i in X:
if np.linalg.norm(np.array(i) - point_1) <= np.linalg.norm(np.array(i) - point_2):
cluster_0.append(np.array(i))
else:
cluster_1.append(np.array(i))
if np.array(cluster_0).size == 0:
print(None)
else:
mean_1 = np.mean(cluster_0[:], axis = 0)
print(np.round(mean_1, 2))
if np.array(cluster_1).size == 0:
print(None)
else:
mean_2 = np.mean(cluster_1[:], axis = 0)
print(np.round(mean_2, 2))