scipy.sparse.csr.csr_matrix:Matrix扩展

Question

我正在使用sklearn做机器学习，works.Here是我的两个变量：

>>> matrix
<1397x9576 sparse matrix of type '<type 'numpy.float64'>'
        with 44655 stored elements in Compressed Sparse Row format>

>>> type(density)
<type 'list'>
>>> len(density)
1397

matrix是由TfidfVectorizer.fit_transform()生成的。我想通过添加变量matrix来扩展变量density，作为一个新的column.Is，有实现它的方法吗？

Answer 1

用枕木堆对柱密度进行矩阵叠加

from scipy.sparse import hstack
new_matrix = hstack([matrix, density])

Answer 2

下面是向矩阵中添加另一列的正确方法

 from scipy.sparse import hstack
 import numpy as np     
 from scipy.sparse import csr_matrix
 density_2 = np.array(density)
 density_3 = csr_matrix(density_2)
 density_4 = density_3.transpose()
 new_matrix = hstack([matrix, density_4])