title: How to make a histogram from a list of data
body: <p>Well I think matplotlib got downloaded but with my new script I get this error:</p>
  
  <pre><code>/usr/lib64/python2.6/site-packages/matplotlib/backends/backend_gtk.py:621:     DeprecationWarning: Use the new widget gtk.Tooltip
    self.tooltips = gtk.Tooltips()
  Traceback (most recent call last):
    File "vector_final", line 42, in &lt;module&gt;
  plt.hist(data, num_bins)
    File "/usr/lib64/python2.6/site-packages/matplotlib/pyplot.py", line 2008, in hist
  ret = ax.hist(x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, **kwargs)
    File "/usr/lib64/python2.6/site-packages/matplotlib/axes.py", line 7098, in hist
  w = [None]*len(x)
  TypeError: len() of unsized object
  </code></pre>
  
  <p>And my code is:
      #!/usr/bin/python</p>
  
  <pre><code>l=[]
  with open("testdata") as f:
      line = f.next()
      f.next()# skip headers
      nat = int(line.split()[0])
      print nat
  
      for line in f:
          if line.strip():
            if line.strip():
              l.append(map(float,line.split()[1:]))  
  
  
      b = 0
      a = 1
  for b in range(53):
      for a in range(b+1,54):
          import operator
          import matplotlib.pyplot as plt
          import numpy as np
  
          vector1 = (l[b][0],l[b][1],l[b][2])
          vector2 = (l[a][0],l[a][1],l[a][2])
  
              x = vector1
              y = vector2
              vector3 = list(np.array(x) - np.array(y))
              dotProduct = reduce( operator.add, map( operator.mul, vector3, vector3))
  
  
          dp = dotProduct**.5
          print dp
  
          data = dp
          num_bins = 200 # &lt;- number of bins for the histogram
          plt.hist(data, num_bins)
          plt.show()
  </code></pre>
  
  <p>But the code thats getting me the error is the new addition that I added which is the last part, reproduced below:</p>
  
  <pre><code>                data = dp
                  num_bins = 200 # &lt;- number of bins for the histogram
                  plt.hist(data, num_bins)
                  plt.show()
  </code></pre>