import numpy as np
x = np.array([[1,3,5],[-2,-4,-5],[3,6,1]] , dtype = 'int')
m = np.linalg.det(x)
c =[[i for i in range(3)] for j in range(3)]
for i in range(3):
    for j in range(3):
        c[i][j] = (-1)*(i+j)*m

要使c.T工作时没有任何错误，数组c应该是一个numpy数组。这里@TaohidulIslam声明的数组c是一个Python列表。所以你会得到一个错误。
按如下方式声明c：c =np.array([[i for i in range(3)] for j in range(3)])

你可以用下面适用于非奇异矩阵的方法通过转置余因子矩阵来计算伴随矩阵。首先，求出余因子矩阵，如下所示：https://www.geeksforgeeks.org/how-to-find-cofactor-of-a-matrix-using-numpy/然后，求余因子矩阵的转置。

import numpy as np
import math as mth

# get cofactors matrix 
def getcofat(x):
    eps = 1e-6
    detx = np.linalg.det(x)
    if (mth.fabs(detx) < eps):
        print("No possible to get cofactors for singular matrix with this method")
        x = None
        return x
    invx = np.linalg.pinv(x)
    invxT = invx.T
    x = invxT * detx
    return x
# get adj matrix
def getadj(x):
    eps = 1e-6
    detx = np.linalg.det(x)
    if (mth.fabs(detx) < eps):
        print("No possible to get adj matrix for singular matrix with this method")
        adjx = None
        return adjx
    cofatx = getcofat(x)
    adjx = cofatx.T
    return adjx

A = np.array([[1, 3, 5], [-2, -4, -5], [3, 6, 1]])
print(A)
print(np.linalg.det(A))
Acofat = getcofat(A)
print(Acofat)
Aadj = getadj(A)
print(Aadj)