title: Drop multiple columns in pandas
body: <p>I am trying to drop multiple columns (column 2 and 70 in my data set, indexed as 1 and 69 respectively) by index number in a pandas data frame with the following code:</p>
  
  <pre><code>df.drop([df.columns[[1, 69]]], axis=1, inplace=True)
  </code></pre>
  
  <p>I get the following error: </p>
  
  <pre><code>TypeError: unhashable type: 'Index'
  </code></pre>
  
  <p>And in my code the [1, 69] is highlighted and says:</p>
  
  <pre><code>Expected type 'Integral', got 'list[int]' instead
  </code></pre>
  
  <p>The following code does what I want it to do successfully, but on two lines of repetitive code (first dropping col index 69, then 1, and order does matter because dropping earlier columns changes the index of later columns). I thought I could specify more than one column index simply as a list, but perhaps I have something wrong above?</p>
  
  <pre><code>df.drop([df.columns[69]], axis=1, inplace=True)
  df.drop([df.columns[1]], axis=1, inplace=True)
  </code></pre>
  
  <p>Is there a way that I can do this on one line similar to the first code snippet above?</p>