title: How to apply multiple masks to a dataframe at the same time?
body: <p>I have set up three masks for my <code>df</code>, and I want to filter out these values. </p>
  
  <p>For example, some random masks:</p>
  
  <pre><code>mask1 = df['column1'].isnull()
  mask2 = df['column2'] &gt; 5
  mask3 = df['column3'].str.contains('hello')
  </code></pre>
  
  <p>Now how do I combine these masks to filter <strong>out</strong> these values? 
  Is this the correct way? Using both <code>~</code> and <code>|</code> ?</p>
  
  <pre><code>masked_df = df[~mask1 | ~mask2 | ~mask3]
  </code></pre>
  
  <p>I have so many rows in my dataframe that I can't be 100% sure with manual checking to see if it's correct. </p>