How do I filter rows in a dataframe that have whole numbers in one column
<p>I am new to Python and Pandas and I am struggling a bit with this.</p>

<p>I have a set of data with an <code>Age</code> column of type <code>float64</code>.  Some of the values have a fractional part and some do not.  I want to remove all the rows that have whole number values for <code>Age</code>.</p>

<p>This was my attempt at it:</p>

<pre><code>estimatedAges = train[int(train['Age']) &lt; train['Age']]
</code></pre>

<p>But I got this error:</p>

<blockquote>
  <p>TypeError                                 Traceback (most recent call last)
   in ()
        1 #estimatedAges = train[train['Age'] > 1]
  ----> 2 estimatedAges = train[int(train['Age']) &lt; train['Age']]
        3 estimatedAges.info()</p>
  
  <p>C:\Anaconda3\lib\site-packages\pandas\core\series.py in wrapper(self)
       76             return converter(self.iloc[0])
       77         raise TypeError("cannot convert the series to "
  ---> 78                         "{0}".format(str(converter)))
       79 
       80     return wrapper</p>
  
  <p>TypeError: cannot convert the series to &lt;class 'int'`></p>
</blockquote>

<p>So, it looks like <code>int()</code> does not work on series data and I am going to have to find another approach, I'm just not sure what that other approach is.</p>