权重系数（灰色关联法）python

import pandas as pd
import numpy as np

x = pd.DataFrame([[2000,0.732,0.836,0.628,0.743], [2001,0.758,0.883,0.688,0.787], [2002,0.859,0.914,0.781,0.929],[2003,1.0125,1.0440,1.0237,0.9847],[2004,1.2356,1.1069,1.2833,1.2363],[2005,1.4013,1.2152,1.5405,1.3182]])

x=pd.read_excel(‘D:\date\winequality\winequality-red1.xlsx’)

x=df.iloc[:,1:].T

1、数据均值化处理

x_mean=x.mean(axis=1)
for i in range(x.index.size):
x.iloc[i,:] = x.iloc[i,:]/x_mean[i]

x.iloc[i,:] = x.iloc[i,:]/x_mean[i]

2、提取参考队列和比较队列

ck=x.iloc[0,:]
cp=x.iloc[1:,:]

比较队列与参考队列相减

t=pd.DataFrame()
for j in range(cp.index.size):
temp=pd.Series(cp.iloc[j,:]-ck)
t=t.append(temp,ignore_index=True)

#求最大差和最小差
mmax=t.abs().max().max()
mmin=t.abs().min().min()
rho=0.5

#3、求关联系数
ksi=((mmin+rhommax)/(abs(t)+rhommax))

#4、求关联度
r=ksi.sum(axis=1)/ksi.columns.size

#5、关联度排序，得到结果r3>r2>r1
result=r.values
print(result)
result.shape