title: pandas: combine two columns in a DataFrame
body: <p>I have a pandas <code>DataFrame</code> that has multiple columns in it:</p>
  
  <pre><code>Index: 239897 entries, 2012-05-11 15:20:00 to 2012-06-02 23:44:51
  Data columns:
  foo                   11516  non-null values
  bar                   228381  non-null values
  Time_UTC              239897  non-null values
  dtstamp               239897  non-null values
  dtypes: float64(4), object(1)
  </code></pre>
  
  <p>where <code>foo</code> and <code>bar</code> are columns which contain the same data yet are named differently. Is there are a way to move the rows which make up <code>foo</code> into <code>bar</code>, ideally whilst maintaining the name of <code>bar</code>? </p>
  
  <p>In the end the DataFrame should appear as:</p>
  
  <pre><code>Index: 239897 entries, 2012-05-11 15:20:00 to 2012-06-02 23:44:51
  Data columns:
  bar                   239897  non-null values
  Time_UTC              239897  non-null values
  dtstamp               239897  non-null values
  dtypes: float64(4), object(1)
  </code></pre>
  
  <p>That is the NaN values that made up bar were replaced by the values from <code>foo</code>.</p>