title: Pandas: boolean indexing with unequal Series lengths
body: <p>Given two pandas series objects A and Matches. Matches contains a subset of the indexes of A and has boolean entries. How does one do the equivalent of logical indexing?</p>
  
  <p>If Matches were the same length as A, one could just use:</p>
  
  <pre><code>A[Matches] = 5.*Matches
  </code></pre>
  
  <p>With Matches shorter than A one gets:</p>
  
  <pre><code>error: Unalignable boolean Series key provided
  </code></pre>
  
  <hr>
  
  <h2>Edit 1: Illustration as requested</h2>
  
  <pre><code>In [15]: A = pd.Series(range(10))
  
  In [16]: A
  Out[16]: 0    0
  1    1
  2    2
  3    3
  4    4
  5    5
  6    6
  7    7
  8    8
  9    9
  dtype: int64
  
  In [17]: Matches = (A&lt;3)[:5]
  
  In [18]: Matches
  Out[18]: 0     True
  1     True
  2     True
  3    False
  4    False
  dtype: bool
  
  In [19]: A[Matches] = None
  ---------------------------------------------------------------------------
  IndexingError                             Traceback (most recent call last)
  &lt;ipython-input-19-7a04f32ce860&gt; in &lt;module&gt;()
  ----&gt; 1 A[Matches] = None
  
  C:\Anaconda\lib\site-packages\pandas\core\series.py in __setitem__(self, key, value)
      631 
      632         if _is_bool_indexer(key):
  --&gt; 633             key = _check_bool_indexer(self.index, key)
      634             try:
      635                 self.where(~key, value, inplace=True)
  
  C:\Anaconda\lib\site-packages\pandas\core\indexing.py in _check_bool_indexer(ax, key)
     1379         mask = com.isnull(result.values)
     1380         if mask.any():
  -&gt; 1381             raise IndexingError('Unalignable boolean Series key provided')
     1382 
     1383         result = result.astype(bool).values
  
  IndexingError: Unalignable boolean Series key provided
  
  In [20]: 
  </code></pre>
  
  <p>The result I am looking for is:</p>
  
  <pre><code>In [16]: A
  Out[16]: 0    None
  1    None
  2    None
  3    3
  4    4
  5    5
  6    6
  7    7
  8    8
  9    9
  dtype: int64
  </code></pre>
  
  <p>The construction of the Matches series is artificial and for illustration only. Also, in my case row indexes are obviously non-numeric and not equal to element values...</p>