function result=cwfac(vector); 
fprintf('相关系数矩阵:\n') 
std=CORRCOEF(vector)        %计算相关系数矩阵 
fprintf('特征向量(vec)及特征值(val)：\n') 
[vec,val]=eig(std)   %求特征值(val)及特征向量(vec) 
newval=diag(val) ; 
[y,i]=sort(newval) ;     %对特征根进行排序，y 为排序结果，i 为索引 
fprintf('特征根排序：\n') 
for z=1:length(y) 
     newy(z)=y(length(y)+1-z); 
end 

{
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.read_csv('./data/file1.csv')\n",
    "df4 = pd.read_csv('./data/file4.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_11 = df1[['carid','price']]\n",
    "df4 = df_11.merge(df4,on='carid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1 数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,