import numpy as np import pandas as pd data = pd.read_csv("data/预处理.csv", header=None); data = np.array(data) cluster = [] # 按第二个到第十四个标签分类 for i in range(178): if len(cluster) == 0: cluster.append([0]) else: m = 0 for j in range(len(cluster)): n = 0 for x in range(1, 14): if data[i][x] == data[j][x]: n = n + 1 if n == 2: cluster[j].append(i) m = 1 if m == 0: cluster.append([i]) for i in range(len(cluster)): for j in range(len(cluster)): if cluster[i] == cluster[j] and i != j: cluster[j] = 0 for i in range(len(cluster)): print( cluster[i]) xiu1 = [] for t in range(178): if data[t][0] ==1: xiu1.append(t) xiu2 = [] for t in range(178): if data[t][0] == 2: xiu2.append(t) xiu3 = [] for t in range(178): if data[t][0] == 3: xiu3.append(t) print(xiu1) print(xiu2) print(xiu3)修改并完善代码，只用简单的for循环不用decision，使他能分别输出xiu1,xiu2,xiu3在所有13个条件属性的下近似，

你可以使用以下代码来修改并完善你的代码，以输出xiu1、xiu2和xiu3在所有13个条件属性下的近似值：

import numpy as np
import pandas as pd

data = pd.read_csv("data/预处理.csv", header=None)
data = np.array(data)
cluster = []
# 按第二个到第十四个标签分类
for i in range(178):
    if len(cluster) == 0:
        cluster.append([0])
    else:
        m = 0
        for j in range(len(cluster)):
            n = 0
            for x in range(1, 14):
                if data[i][x] == data[j][x]:
                    n = n + 1
            if n == 2:
                cluster[j].append(i)
                m = 1
        if m == 0:
            cluster.append([i])

xiu1 = []
for t in range(178):
    if data[t][0] == 1:
        xiu1.append(t)

xiu2 = []
for t in range(178):
    if data[t][0] == 2:
        xiu2.append(t)

xiu3 = []
for t in range(178):
    if data[t][0] == 3:
        xiu3.append(t)

# 计算xiu1在所有13个条件属性下的近似值
approximations_xiu1 = []
for col in range(1, 14):  # 遍历所有13个条件属性列
    approx = sum(data[t][col] for t in xiu1) / len(xiu1)  # 计算平均值作为近似值
    approximations_xiu1.append(approx)

# 计算xiu2在所有13个条件属性下的近似值
approximations_xiu2 = []
for col in range(1, 14):  # 遍历所有13个条件属性列
    approx = sum(data[t][col] for t in xiu2) / len(xiu2)  # 计算平均值作为近似值
    approximations_xiu2.append(approx)

# 计算xiu3在所有13个条件属性下的近似值
approximations_xiu3 = []
for col in range(1, 14):  # 遍历所有13个条件属性列
    approx = sum(data[t][col] for t in xiu3) / len(xiu3)  # 计算平均值作为近似值
    approximations_xiu3.append(approx)

print("xiu1 近似值：", approximations_xiu1)
print("xiu2 近似值：", approximations_xiu2)
print("xiu3 近似值：", approximations_xiu3)

这样，你就可以得到xiu1、xiu2和xiu3在所有13个条件属性下的近似值。希望这能帮到你！