title: pandas - different dtype column before/after reading a file
body: <p>I'm referring to <a href="https://stackoverflow.com/questions/35746039/pandas-get-nested-string-values-from-arrays">this</a> question since I'm facing with a weird behaviour of column types before and after reading the same dataframe from a .csv. Starting from:</p>
  
  <pre><code>In [137]: df
  Out[137]: 
      node1  node2 lang  w c1 c2
  0       1      2   it  1  a  a
  1       1      2   en  1  a  a
  2       2      3   es  2  a  b
  3       3      4   it  1  b  b
  4       5      6   it  1  c  c
  5       3      5   tg  1  b  c
  6       1      7   it  1  a  a
  7       7      1   es  1  a  a
  8       3      8   es  1  b  b
  9       8      4   es  1  b  b
  10      1      9   it  1  a  a
  </code></pre>
  
  <p>Then performing a groupby:</p>
  
  <pre><code>In [138]: g = df.groupby(['c1','c2'])['lang'].unique().reset_index()
  
  In [139]: g
  Out[139]: 
    c1 c2          lang
  0  a  a  [it, en, es]
  1  a  b          [es]
  2  b  b      [it, es]
  3  b  c          [tg]
  4  c  c          [it]
  </code></pre>
  
  <p>and get the values of the <code>lang</code> column returns:</p>
  
  <pre><code>In [148]: g['lang'].values
  Out[148]: 
  array([array(['it', 'en', 'es'], dtype=object),
         array(['es'], dtype=object), array(['it', 'es'], dtype=object),
         array(['tg'], dtype=object), array(['it'], dtype=object)], dtype=object)
  </code></pre>
  
  <p>Then if I:</p>
  
  <pre><code>In [141]: g.to_csv('g.csv',index=False)
  
  In [142]: g = pd.read_csv('g.csv')
  
  In [143]: g
  Out[143]: 
    c1 c2              lang
  0  a  a  ['it' 'en' 'es']
  1  a  b            ['es']
  2  b  b       ['it' 'es']
  3  b  c            ['tg']
  4  c  c            ['it']
  
  In [145]: g['lang'].values
  Out[145]: array(["['it' 'en' 'es']", "['es']", "['it' 'es']", "['tg']", "['it']"], dtype=object)
  </code></pre>
  
  <p>So reading the file from .csv leads to an array of string which is more complex to handle than the original array of arrays before writing/reading the dataframe. Anyone knows whether there is a way to keep the same format after reading the dataframe from file?</p>