title: Full outer join of two or more data frames
body: <p>Given the following three Pandas data frames, I need to merge them similar to an SQL full outer join. Note that the key is multi-index <code>type_N</code> and <code>id_N</code> with <code>N</code> = 1,2,3:</p>
  
  <pre><code>import pandas as pd
  
  raw_data = {
          'type_1': [0, 1, 1,1],
          'id_1': ['3', '4', '5','5'],
          'name_1': ['Alex', 'Amy', 'Allen', 'Jane']}
  df_a = pd.DataFrame(raw_data, columns = ['type_1', 'id_1', 'name_1' ])
  
  raw_datab = {
          'type_2': [1, 1, 1, 0],
          'id_2': ['4', '5', '5', '7'],
          'name_2': ['Bill', 'Brian', 'Joe', 'Bryce']}
  df_b = pd.DataFrame(raw_datab, columns = ['type_2', 'id_2', 'name_2'])
  
  raw_datac = {
          'type_3': [1, 0],
          'id_3': ['4', '7'],
          'name_3': ['School', 'White']}
  df_c = pd.DataFrame(raw_datac, columns = ['type_3', 'id_3', 'name_3'])
  </code></pre>
  
  <p>The expected result should be:</p>
  
  <pre><code>type_1   id_1   name_1   type_2   id_2   name_2   type_3   id_3   name_3
  0        3      Alex     NaN      NaN    NaN      NaN      NaN    NaN
  1        4      Amy      1        4      Bill     1        4      School
  1        5      Allen    1        5      Brian    NaN      NaN    NaN
  1        5      Allen    1        5      Joe      NaN      NaN    NaN
  1        5      Jane     1        5      Brian    NaN      NaN    NaN
  1        5      Jane     1        5      Joe      NaN      NaN    NaN
  NaN      NaN    NaN      0        7      Bryce    0        7      White
  </code></pre>
  
  <p>How can this be achieved in Pandas?    </p>