title: Append a list of values with mixed types in Python to data frame
body: <p>I have a data frame reading from csv using pandas.read_csv, each row of data frame looks like this:</p>
  
  <pre><code>[1, '10/18/2016 06:00', 1, 14, 0, 5.5]
  </code></pre>
  
  <p>Basically, it consists of integers, string, and floats. Now, I want to generate more data (newrow) based on existing data and append to the original data frame. When I try to call function <code>append</code> with the following code:</p>
  
  <pre><code>df.append(list(newrow))
  </code></pre>
  
  <p>I got the error: </p>
  
  <pre><code>RuntimeWarning: unorderable types: str() &lt; int(), sort order is undefined for incomparable objects. 
  result = result.union(other)
  </code></pre>
  
  <p>I think the string type is playing naughty here, but I did not figure out a way to achieve this. </p>
  
  <p>In addition, I also tried to convert the <code>df</code> to <code>df.values</code> first, and then use <code>numpy.vstack(df.values, numpy.array(newrow))</code>. However, the result of this code becomes</p>
  
  <pre><code>['1', '10/18/2016 06:00', '1', '14', '0', '5.5']
  </code></pre>
  
  <p>in which all fields become strings. Any help is appreciated.</p>