title: Pandas: Sum of two boolean series
body: <p>In Python:</p>
  
  <pre><code>In [1]: True+True
  Out[1]: 2
  </code></pre>
  
  <p>So after the following set-up:</p>
  
  <pre><code>import pandas as pd
  ser1 = pd.Series([True,True,False,False])
  ser2 = pd.Series([True,False,True,False])
  </code></pre>
  
  <p>What I want is to find the element-wise sum of <code>ser1</code> and <code>ser2</code>, with the booleans treated as integers for addition as in the Python example. </p>
  
  <p>But Pandas treats the addition as an element-wise "or" operator, and gives the following (undesired) output:</p>
  
  <pre><code>In [5]: ser1+ser2
  */lib/python2.7/site-packages/pandas/computation/expressions.py:184: UserWarning: evaluating in Python space because the '+' operator is not supported by numexpr for the bool dtype, use '|' instead
    unsupported[op_str]))
  Out[5]: 
  0     True
  1     True
  2     True
  3    False
  dtype: bool
  </code></pre>
  
  <p>I know I get can get my <strong>desired</strong> output using <code>astype(int)</code> on either series:</p>
  
  <pre><code>In [6]: ser1.astype(int) + ser2
  Out[6]: 
  0    2
  1    1
  2    1
  3    0
  dtype: int64
  </code></pre>
  
  <p>Is there another (more "pandonic") way to get the [2,1,1,0] series? Is there a good explanation for why simple Series addition doesn't work here?</p>