title: Ignoring duplicate entries in sparse matrix
body: <p>I've tried to initialize <code>csc_matrix</code> and <code>csr_matrix</code> from a list of <code>(data, (rows, cols))</code> values as the documentation suggests. </p>
  
  <pre><code>sparse = csc_matrix((data, (rows, cols)), shape=(n, n))
  </code></pre>
  
  <p>The problem is that, the method that I actually have for generating the <code>data</code>, <code>rows</code> and <code>cols</code> vectors introduces duplicates for some points. By default, scipy adds the values of the duplicate entries. However, in my case, those duplicates have exactly the same value in <code>data</code> for a given <code>(row, col)</code>.</p>
  
  <p>What I'm trying to achieve is to make scipy ignore the second entry if already exists one, instead of adding them.</p>
  
  <p>Ignoring the fact that I could improve the generation algorithm to avoid generating duplicates, is there a parameter or another way of creating a sparse matrix that ignores duplicates?</p>
  
  <p>Currently two entries with <code>data = [4, 4]; cols = [1, 1]; rows = [1, 1];</code> generate a sparse matrix which value at <code>(1,1)</code> is <code>8</code> while the desired value is <code>4</code>.</p>
  
  <pre><code>&gt;&gt;&gt; c = csc_matrix(([4, 4], ([1,1],[1,1])), shape=(3,3))
  &gt;&gt;&gt; c.todense()
  matrix([[0, 0, 0],
          [0, 8, 0],
          [0, 0, 0]])
  </code></pre>
  
  <p>I'm also aware that I could filter them by using a 2-dimensional numpy <code>unique</code> function, but lists are quite large so this is not really a valid option.</p>
  
  <p>Other possible answer to the question: Is there any way of specifying what to do with duplicates? i.e. keeping the <code>min</code> or <code>max</code> instead of the default <code>sum</code>?</p>