title: How to drop DataFrame columns based on dtype
body: <p>I've got a pandas dataframe and I'm trying to drop all the object fields from so that I'm left with only numeric.</p>
  
  <p>I've been trying to write a for loop to do this task, as I'm likely going to need to do it over and over again with different data. </p>
  
  <p>For some reason I can't get it working. Below is what I've did so far</p>
  
  <pre><code>for cols in data:
      if data.values.type == object:
          numdata = data.drop(axis=1, inplace=True)
  </code></pre>
  
  <p>The error I get is:</p>
  
  <blockquote>
    <p>AttributeError                            Traceback (most recent call
    last)  in ()
          1 for cols in data:
    ----> 2     if data.values.type == object:
          3         numdata = data.drop(axis=1, inplace=True)</p>
    
    <p>AttributeError: 'numpy.ndarray' object has no attribute 'type'</p>
  </blockquote>
  
  <p>I am a newb and for some reason I can't get the for loop and if statement logic to stick in my head.</p>