title: Parsing Dataframe with nested lists and dicts?
body: <p>I'm pretty new to pandas/python and currently stuck doing this parsing.
  Parsing Dataframe with nested lists and dicts</p>
  
  <p>DF:</p>
  
  <pre><code>    a       b       c             d         e        f          
  
  0   1       2   {'county':        3         4       [{'name': 'essex,england','locality': None,'region':'harlow','subregion':None}]
                 'cleveland', 
               'country': 
                  'england'}       
  
  1   4       5   {'county':        6         7       [{'name': 'hampsire,england','locality': None,'region':'alton','subregion':None}]
                 'hamphsire', 
               'country': 
                  'england'}
  </code></pre>
  
  <p>Output should be:</p>
  
  <pre><code>     a      b    county     country      d       e      name        locality       region         subregion 
  
  0   1      2   cleveland    england      3       4      essex,england      None      harlow         None
  
  
  1   4      5   hamphsire    england      6        7     hampsire,england   None      alton         None
  </code></pre>
  
  <p>What i have tried/Known:
  I parsed the df if only a single row present and been successful, but two rows i couldn't do it. 
  How i parsed a single row : create a function and expand it then merge into df</p>
  
  <p>Original dict if needed:</p>
  
  <p>F column:</p>
  
  <pre><code>   [{'name': 'essex, england',
  'locality': None,
  'region': 'harlow',
  'subregion': None,
  </code></pre>
  
  <p>c column</p>
  
  <pre><code>'location': {0: {'county': 'cleveland',
                     'country': 'england'} 
  </code></pre>