Pandas Pandas Pandas

Question

I am outputting the correct centroids for the test cases, but they are not being taken as correct. Can someone advise?

n = int(input())

import numpy as np
X = []
for i in range(n):
X.append([float(x) for x in input().split()])
#print(X)

#calculate distance between points and the origin
dist_origin = []
for i in range(n):
y = np.sqrt((X[i][0])**2 + (X[i][1]**2))
dist_origin.append(float(y))

#calculate distance between points and second centroid
dist_cen = []
for i in range(n):
y = np.sqrt((X[i][0] - 2.0)**2 + (X[i][1] - 2.0)**2)
dist_cen.append(float(y))

#assign points to centroid
origin = []
cen = []
for i in range(n):
if dist_origin[i] < dist_cen[i]:
origin.append(X[i])
elif dist_origin[i] > dist_cen[i]:
cen.append(X[i])
elif dist_origin[i] == dist_cen[i]:
origin.append(X[i])
else:
print(none)

#calculate new centroids from assigned data points
x = len(origin)
xsum, ysum = 0,0
for i in range(x):
xsum += origin[i][0]
ysum += origin[i][1]
xavg = round(xsum / x, 2)
yavg = round(ysum / x, 2)
cen1 = [xavg, yavg]

x = len(cen)
xsum, ysum = 0,0
for i in range(x):
xsum += cen[i][0]
ysum += cen[i][1]
xavg = round(xsum / x, 2)
yavg = round(ysum / x, 2)
cen2 = [xavg, yavg]

print(cen1)
print(cen2)

Answer 1

https://www.sololearn.com/compiler-playground/cvUcsMq6W81C

import numpy as np

n, k, datapoints = int(input()), 2, []
for i in range(n):
datapoints.append([float(x) for x in input().split()])
datapoints = np.array(datapoints)

centroids = np.array([[0, 0], [2, 2]])

def euclidean_distance(x, y):
return np.sum(np.square(x - y))

ed = np.zeros((n, k))
for i, c in enumerate(centroids):
for j, d in enumerate(datapoints):
ed[j, i] = euclidean_distance(c, d)
nearest_c = np.argmin(ed, axis=1)

for c in range(k):
dps = datapoints[np.asarray(c==nearest_c).nonzero()]
if len(dps) == 0:
print(None)
continue
new_centroid = dps.mean(axis=0).round(2)
print(new_centroid)