Data Science Last Code Project-Pandas Pandas Pandas

Question

The Project called "Pandas Pandas Pandas", so I think it should be done by Pandas.
It could be done completely by Pandas.
But one issue is the output format. Only the Numpy array.round() could output the format like [4. 0.], which the trailing zero had been automatiically removed.

=====================================================================
import pandas as pd
import numpy as np

n = int(input())

df_ori_cen = pd.DataFrame(
{"cen_1st": [0, 0],
"cen_2nd": [2, 2]},
index = [0, 1])

df_con_input = pd.DataFrame()

for i in range(n):
df_temp = pd.DataFrame(
[float(x) for x in input().split()], columns = [i])
df_con_input = pd.concat([df_con_input, df_temp],axis = 1 )

df_first_cen = pd.DataFrame()
df_second_cen = pd.DataFrame()

for i in range(n):
ed1 = sum((df_ori_cen["cen_1st"] - df_con_input[i])**2)**0.5
ed2 = sum((df_ori_cen["cen_2nd"] - df_con_input[i])**2)**0.5
if ed1 <= ed2:
df_first_cen = pd.concat([df_first_cen, pd.DataFrame(df_con_input[i])], axis = 1)
else:
df_second_cen = pd.concat([df_second_cen, pd.DataFrame(df_con_input[i])], axis = 1)

if df_first_cen.empty != True:
new_cen_first = df_first_cen.mean(axis = 1)
array_cen_first = np.round([*new_cen_first], 2)
print(array_cen_first)
else:
print(None)

if df_second_cen.empty != True:
new_cen_second = df_second_cen.mean(axis = 1)
array_cen_second = np.round([*new_cen_second], 2)
print(array_cen_second)
else:
print(None)

Answer 1

Yaodong Song So what is your question?