title: Drop few rows of a pandas dataframe using lambda
body: <p>I'm currently facing a problem with method chaining in manipulating data frames in pandas, here is the structure of my data:</p>
  
  <pre><code>import pandas as pd
  
  lst1 = range(100)
  lst2 = range(100)
  lst3 = range(100)
  df = pd.DataFrame(
      {'Frenquency': lst1,
       'lst2Tite': lst2,
       'lst3Tite': lst3
      })
  </code></pre>
  
  <p>the question is get entries(rows) if the frequency is less than 6, but it needs to be done in method chaining.</p>
  
  <p>I know using a traditional way is easy, I could just do</p>
  
  <p><code>df[df["Frenquency"]&lt;6]</code></p>
  
  <p>to get the answer.</p>
  
  <p>However, the question is about how to do it with method chaining, I tried something like </p>
  
  <p><code>df.drop(lambda x:x.index if x["Frequency"] &lt;6 else null)</code></p>
  
  <p>but it raised an error <code>"[&lt;function &lt;lambda&gt; at 0x7faf529d3510&gt;] not contained in axis"</code></p>
  
  <p>Could anyone share some light on this issue?</p>