title: How to get pandas.DataFrame columns containing specific dtype
body: <p>I'm using df.columns.values to make a list of column names which I then iterate over and make charts, etc... but when I set this up I overlooked the non-numeric columns in the df. Now, I'd much rather not simply drop those columns from the df (or a copy of it). Instead, I would like to find a slick way to eliminate them from the list of column names. </p>
  
  <p>Now I have: </p>
  
  <pre><code>names = df.columns.values 
  </code></pre>
  
  <p>what I'd like to get to is something that behaves like: </p>
  
  <pre><code>names = df.columns.values(column_type=float64) 
  </code></pre>
  
  <p>Is there any slick way to do this? I suppose I could make a copy of the df, and drop those non-numeric columns before doing columns.values, but that strikes me as clunky.</p>
  
  <p>Welcome any inputs/suggestions. Thanks. </p>