title: Remove pandas dataframe row if one column's element is non-numeric
body: <p>I have been searching for an answer for this simple thing for an hour now. I have a pandas dataframe that looks like this:</p>
  <pre><code>   title      |   price
  
  &quot;some text 1&quot;     124.5
  &quot;some text 2&quot;     543.2
  &quot;some text 3&quot;     156.2
  &quot;some text 4&quot;     &quot;Price N/A&quot;
  &quot;some text 5&quot;     216.7
  </code></pre>
  <p>I want to remove the rows that don't contain an actual float price. I tried the suggestion from <a href="https://stackoverflow.com/a/33975750/5016028">this answer</a>:</p>
  <pre><code>raw_data[raw_data.price.apply(lambda x: x.isnumeric())]
  </code></pre>
  <p>and I get:</p>
  <pre><code>AttributeError: 'float' object has no attribute 'isnumeric'
  </code></pre>
  <p>Nothing seems to work for such a simple operation. I tried pretty much all the answers I found on stack and elsewhere.</p>