title: Each item in DataFrame column is list of different dimension - how to proceed?
body: <p>My issue is similar to <a href="https://stackoverflow.com/questions/12253447/converting-a-list-of-ints-tuples-into-an-numpy-array">Converting a list of ints, tuples into an numpy array</a> but different in that each item is not necessarily of the format [float, (float, float, float)] but the first is [float, float] and the next is [float, float, float], etc.</p>
  
  <p>The data in my DataFrame is obtained from querying a mySQL database, if that matters. The 'values' column was originally populated by strings of the format "1,2" and "1,2,3" and "1,2,3,4,5" and so on.
  The DataFrame now looks roughly like:</p>
  
  <pre><code>ID       values            num
  1        [1, 2]             2
  2        [1, 2, 3]          3
  3        [1, 2, 3, 4, 5]    5
  </code></pre>
  
  <p>What I want to do is be able to take each [float, float, ...] entry from the DataFrame and report new values/variables based off of it to new columns appended to the same DataFrame, such as calculate the standard deviation of each 'values' list or the new variable ' avg = sum(values)/num ' and store the results in df_new['stddev'] or df_new['avg'].</p>
  
  <p>And here's the portion of my code I'm focusing on so far:</p>
  
  <pre><code>df_new = df[df.num &lt;= 10]
  df_new['values'] = df_new['values'].astype(str).str.split(',')
  valList = df_new.values.tolist()
  </code></pre>
  
  <p>I'm relatively new to Python so bear with me if I'm missing out on something basic.</p>