title: assigning points to bins
body: <p>What is a good way to bin numerical values into a certain range? For example, suppose I have a list of values and I want to bin them into N bins by their range.  Right now, I do something like this:</p>
  
  <pre><code>from scipy import *
  num_bins = 3 # number of bins to use
  values = # some array of integers...
  min_val = min(values) - 1
  max_val = max(values) + 1
  my_bins = linspace(min_val, max_val, num_bins)
  # assign point to my bins
  for v in values:
    best_bin = min_index(abs(my_bins - v))
  </code></pre>
  
  <p>where min_index returns the index of the minimum value. The idea is that you can find the bin the point falls into by seeing what bin it has the smallest difference with.</p>
  
  <p>But I think this has weird edge cases. What I am looking for is a good representation of bins, ideally ones that are half closed half open (so that there is no way of assigning one point to two bins), i.e.</p>
  
  <pre><code>bin1 = [x1, x2)
  bin2 = [x2, x3)
  bin3 = [x3, x4)
  etc...
  </code></pre>
  
  <p>what is a good way to do this in Python, using numpy/scipy?  I am only concerned here with binning integer values.</p>
  
  <p>thanks very much for your help.</p>