title: Broadcast pandas.Series.div column-wise to a DataFrame
body: <p>I have an operation that works fine, but is generating a:</p>
  
  <pre><code>FutureWarning: TimeSeries broadcasting along DataFrame index by default 
  is deprecated.
  </code></pre>
  
  <p>So I'd like to do the calculation in a way that is coherent with future versions.</p>
  
  <p>I have a <code>pandas.Series</code> and I'd like to divide that <code>Series</code> by each column of a <code>pandas.DataFrame</code>.</p>
  
  <p>So let's say I have and <code>Series</code>, and a <code>DataFrame</code>, with the following shapes:</p>
  
  <pre><code>In [15]: my_series.shape
  Out[15]: (1504,)
  
  In [16]: my_df.shape
  Out[16]: (1504, 4)
  </code></pre>
  
  <p>When I run <code>my_series/my_df</code> I get the desired result:</p>
  
  <pre><code>In [17]: (my_series/my_df).shape
  Out[17]: (1504, 4)
  </code></pre>
  
  <p>Of course, implementing the <code>pandas.Series.divide</code> operator comes back with an error:</p>
  
  <pre><code>In [18]: my_series.div(my_df)
  ValueError: operands could not be broadcast together with shapes (1504) (1504,4)
  </code></pre>
  
  <p>I've given the <code>series.apply</code> functionality a try, but haven't gotten what I expect (based on how I use <code>pandas.DataFrame.apply</code>):</p>
  
  <pre><code>In [19]: my_series.apply(pandas.Series.divide, my_df)
  Out[19]: ValueError       
  
  In [22]: my_series.apply(pandas.Series.divide, lambda x: my_df[my_df.columns[x]])
  Out[22]: TypeError
  </code></pre>
  
  <p>Any insight, as always, would be greatly appreciated.</p>