title: How to find most frequent values in numpy ndarray?
body: <p>I have a numpy ndarray with shape of (30,480,640), the 1th and 2th axis representing locations(latitude and longitute), the 0th axis contains actual data points.I want to use the most frequent value along the 0th axis at each location, which is to construct a new array with shape of (1,480,640).ie:</p>
  
  <pre><code>&gt;&gt;&gt; data
  array([[[ 0,  1,  2,  3,  4],
          [ 5,  6,  7,  8,  9],
          [10, 11, 12, 13, 14],
          [15, 16, 17, 18, 19]],
  
         [[ 0,  1,  2,  3,  4],
          [ 5,  6,  7,  8,  9],
          [10, 11, 12, 13, 14],
          [15, 16, 17, 18, 19]],
  
         [[40, 40, 42, 43, 44],
          [45, 46, 47, 48, 49],
          [50, 51, 52, 53, 54],
          [55, 56, 57, 58, 59]]])
  
  (perform calculation)
  
  &gt;&gt;&gt; new_data 
  array([[[ 0,  1,  2,  3,  4],
          [ 5,  6,  7,  8,  9],
          [10, 11, 12, 13, 14],
          [15, 16, 17, 18, 19]]])
  </code></pre>
  
  <p>The data points will contain negtive and positive floating numbers. How can I perform such calculations? Thanks a lot!</p>
  
  <p>I tried with numpy.unique,but I got "TypeError: unique() got an unexpected keyword argument 'return_inverse'".I'm using numpy version 1.2.1 installed on Unix and it doesn't support return_inverse..I also tried mode,but it takes forever to process such large amount of data...so is there an alternative way to get the most frequent values? Thanks again.</p>