title: Why does Pandas cut return unequal sized bins?
body: <p>In the <code>Examples</code> section for <a href="https://pandas.pydata.org/docs/reference/api/pandas.cut.html" rel="nofollow noreferrer"><code>pandas.cut</code></a>, the following is mentioned:</p>
  <p><code>Discretize into three equal-sized bins.</code></p>
  <pre><code>pd.cut(np.array([1, 7, 5, 4, 6, 3]), 3)
  
  [(0.994, 3.0], (5.0, 7.0], (3.0, 5.0], (3.0, 5.0], (5.0, 7.0], ...
  Categories (3, interval[float64, right]): [(0.994, 3.0] &lt; (3.0, 5.0] ...
  </code></pre>
  <p>How are the bins equal sized? The first bin seems larger...</p>