title: Pandas: mapping data series (float to string) WITHOUT removal of trailing zeros
body: <p>I am trying to create a data series containing strings of the form:</p>
  
  <p><code>"%.2f +/- %.2f"</code></p>
  
  <p>using two pandas data series (the measurements and their error). Here is how I've implemented this:</p>
  
  <pre><code>df["F"] = df["Fint"].map(str) + " +/- " + df["Fint Err"].map(str)
  </code></pre>
  
  <p>However, the map(str) removes trailing zeros from the values in the series.</p>
  
  <p>E.g for source 'VLA 3 at 6lambda'.</p>
  
  <pre><code>In[101]: df["Fint"]
  Out[101]: 
  Source  Lambda    Fint
  VLA 2   6.0       0.15
          3.6       0.19
  VLA 3   6.0       0.40
          3.6       0.29
  </code></pre>
  
  
  
  <pre><code>In[102]: df["Fint"].map(str)
  Out[102]: 
  Source  Lambda
  VLA 2   6.0       0.15
          3.6       0.19
  VLA 3   6.0        0.4
  </code></pre>
  
  <p>How do I stop the trailing zeros from being removed? </p>
  
  <p>Obviously as you can see I'm actually working with a data frame (but as map is a data series func I thought this would simplify the question), if there's a way of achieving this with applymap instead I'd be happy to know.</p>
  
  <p>Thanks!</p>