title: Creating a dataframe with vector entries
body: <p>I am trying to create a pandas dataframe where the entry in a single cell is a numpy array. For example, given a list of chemical compounds - A2B3C4, D1A2J3 etc, I create a numpy array for each of them so that:</p>
  
  <pre><code>firstium - A2B3C4 - [2,3,4,0,0,0,0.....]
  
  secondium - D1A2J3 - [2,0,0,1,......3....]
  </code></pre>
  
  <p>I would like to create a dataframe with just two columns - 'name' and 'vec' where name is the string for the name of the compound and vec has the array for the formula. let's say that vec is of dimension 1 x 100.</p>
  
  <pre><code> Name             vec
  firstium          [2,3,4,0,0,0...]
  secondium         [2,0,0,1,.....3.]
  </code></pre>
  
  <p>etc. </p>
  
  <p>What I have been doing so far is to create a dictinary {'name':'vec'} and converting this to a dataframe:</p>
  
  <pre><code> Min_dict={}
  
   for ....:
      ..
      Min_dict[min_name]=vec
  
   Min_Dataframe=pd.DataFrame.from_dict(Min_dict,orient='index')
  </code></pre>
  
  <p>However, this gives me a dataframe with as many columns as the dimension of the array, plus one. So, my dataframe has dimensions data x 101.  I need it to be data x 2</p>
  
  <p>This makes it inconvenient to do processing on the data as I would like to treat each array as one unit of information. Does any one know how to do what I just described?</p>
  
  <p>Thanks!</p>