title: Panda Series Insert Error Missing Positional Argument and Does Not Match Index Length
body: <p>I have a list that I am attempting to prepend a value to, but I am uncertain of  the best approach to doing just that. I have read that <code>.insert()</code> is the best method, but after trying two different variations of the method I can't seem to get it to work.</p>
  
  <p>I have tried </p>
  
  <pre><code>df_full_modified = df_full['date', 'b_clicks', 'b_cpc'].insert(0, ['date', 'b_clicks', 'b_cpc'])
  </code></pre>
  
  <p>which returns</p>
  
  <pre><code>TypeError: insert() missing 1 required positional argument: 'value'
  </code></pre>
  
  <p>and also tried adding in a value for the <code>columns</code> parameter</p>
  
  <pre><code>df_full_modified = df_full['date', 'b_clicks', 'b_cpc'].insert(0, ['date', 'b_clicks', 'b_cpc'], ['date', 'b_clicks', 'b_cpc'])
  </code></pre>
  
  <p>which returns</p>
  
  <pre><code>ValueError: Length of values does not match length of index
  </code></pre>
  
  <p>Am I missing something with trying to map an array to the <code>insert()</code> method?</p>
  
  <p>Here is the format of the data frame <code>df_full</code>:</p>
  
  <pre><code>[['2018-01-01', '72', 2.43], ['2018-01-02', '232', 2.8], ['2018-01-03', '255', 2.6], ...
  </code></pre>
  
  <p>and I am trying to prepend <code>['date', 'b_clicks', 'b_cpc']</code> to make it</p>
  
  <pre><code>[['date', 'b_clicks', 'b_cpc'], ['2018-01-01', '72', 2.43], ['2018-01-02', '232', 2.8], ['2018-01-03', '255', 2.6], ...
  </code></pre>