title: Pandas cut with non-unique labels
body: <p>I'm trying to bin data and apply a float value based on the bin. I thought pandas.cut was the tool for this, but apparently it requires unique values for each bin label.</p>
  
  <pre><code>values = [0.6, 0.5, 0.5, 0.6, 0.8, 0.9]
  bins = [0, 2, 5, 10, 15, 25, 200]
  binned = pd.cut(original_table[field], bins, labels=values)
  
  &gt;&gt;&gt; ValueError: Categorical categories must be unique
  </code></pre>
  
  <p>My data (original_table) is very large and doing anything iteratively is quite slow, which is why cut was an appealing tool.  Is there a workaround to make pd.cut work for this?</p>