title: Filter pandas dataframe rows if any value on a list inside the dataframe is in another list
body: <p>I have a <code>pandas dataframe</code> that contains a list in column split_categories:</p>
  
  <pre><code>df.head()
  
        album_id categories split_categories
      0    66562    480.494       [480, 494]
      1   114582        128            [128]
      2     4846          5              [5]
      3     1709          9              [9]
      4    59239    105.104       [105, 104]
  </code></pre>
  
  <p>I would like to select all the rows where the at least one category in a specific list [480, 9, 104].</p>
  
  <p>Expected output:</p>
  
  <pre><code>  album_id categories split_categories
  0    66562    480.494       [480, 494]
  3     1709          9              [9]
  4    59239    105.104       [105, 104]
  </code></pre>
  
  <p>I manage to do it using <code>apply</code>:</p>
  
  <pre><code>def match_categories(row):
      selected_categories =  [480, 9, 104]
      result = [int(i) for i in row['split_categories'] if i in selected_categories]
      return result
  
  df['matched_categories'] = df.apply(match_categories, axis=1)
  </code></pre>
  
  <p>But this code runs on production and this way takes too long (I run it for multiple columns containing lists)</p>
  
  <p>Is there a way to run something like:</p>
  
  <pre><code>df[~(df['split_categories'].anyvalue.isin([480, 9, 104]))]
  </code></pre>
  
  <p>Thanks</p>