1.矩阵的转置:
a.transpose方法
print(test_score)
print(“after transpose:”)
print(test_score.transpose())
b.T属性:
print(‘after T:’)
print(test_score.T)

2.矩阵的行复制扩展
print(test_score)

#行复制
print(‘行复制:’)
print(np.tile(test_score,[2,1]))
说明:矩阵行数变为原来2倍,列数不变,扩展的行与原来的行元素相同

3.矩阵的列复制扩展
print(test_score)

#列复制
print(‘列复制:’)
print(np.tile(test_score,[1,2]))
说明:
a.矩阵列数变为原来2倍,行数不变,扩展的列与原来的列元素相同
b.可以简写为:np.tile(test_score,2)

4.两个矩阵合并为一个矩阵,列数不变,在行方向(垂直方向)上合并:
#两个数组的行合并:
test_score = np.array([[100,80,50,55],[100,99,98,97]])
print(“test_score:”)
print(test_score)
test_score2 = np.array([[77,66,55,44],[11,22,33,44]])
print(“test_score2:”)
print(test_score2)
print(“test_score+test_score2行合并:”)
print(np.vstack([test_score,test_score2]))
说明:进行行合并的两个矩阵,要求列数必须相同

5.两个矩阵合并为一个矩阵,行数不变,在列方向(水平方向)上合并:
#两个数组的列合并:
test_score = np.array([[100,80,50,55],[100,99,98,97]])
print(“test_score:”)
print(test_score)
test_score2 = np.array([[77,66,55,44],[11,22,33,44]])
print(“test_score2:”)
print(test_score2)
print(“test_score+test_score2列合并:”)
print(np.hstack([test_score,test_score2]))
说明:进行列合并的两个矩阵,要求行数必须相同