title: Calculating kurtosis from a numpy array?
body: <p>I am trying to calculate 'kurtosis', as well as other statistics from a numpy array.
  Calculating Min, Max, Mean and Standard Deviation are easy as I've just done.</p>
  
  <pre><code>import arcpy
  arr = arcpy.RasterToNumPyArray(input_Raster) 
  x = arr
  print 'Min =', x.min()
  print 'Max =', x.max() 
  print 'Mean =', x.mean()
  print 'Standard Deviation =', x.std()
  </code></pre>
  
  <p>Which outputs:</p>
  
  <pre><code>Min = 1.87895
  Max = 16.8343
  Mean = 8.03462
  Standard Deviation = 1.52192
  </code></pre>
  
  <p>But this method doesn't work for Kurtosis!
  As I've tried</p>
  
  <pre><code>print 'Kurtosis =', x.kurtosis()
  </code></pre>
  
  <p>And I get: <strong>AttributeError: 'numpy.ndarray' object has no attribute 'kurtosis'</strong></p>
  
  <p>What would be the simplest code I could use to incorporate into my own to calculate a kurtosis result? Thanks. </p>