擅长:python、mysql、java
<pre><code>import scipy.sparse
rows = [2, 236, 246, 389, 1691]
cols = [117, 3, 34, 2757, 74, 1635, 52]
prod = [(x, y) for x in rows for y in cols] # combinations
r = [x for (x, y) in prod] # x_coordinate
c = [y for (x, y) in prod] # y_coordinate
data = [1] * len(r)
m = scipy.sparse.coo_matrix((data, (r, c)), shape=(100000, 40000))
</code></pre>
<p>我认为它运行良好,不需要循环。我直接跟着<a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.coo_matrix.html#scipy.sparse.coo_matrix" rel="noreferrer">doc</a></p>
<pre><code><100000x40000 sparse matrix of type '<type 'numpy.int32'>'
with 35 stored elements in COOrdinate format>
</code></pre>