title: pandas astype str formatting
body: <p>I have a column in a csv I am reading in with pandas that contains years. Because some of the columns are missing they get NAN and the type of the column is float.</p>
  
  <p>I convert the row to string to do some concatenation but instead of getting 2013 I get 2013.0</p>
  
  <p>I fixed this by doing astype(int).astype(str) instead of just astype(str) But feel this may be wasteful doing double conversions like this.</p>
  
  <p>What is the most efficient way to convert a float dtype column into a string dropping any decimal points that may occur(or rounding either way is fine.)</p>