title: DataFrame concat different column values when index are the same
body: <p>I am working on concat multiple DataFrames(DFs) into one DF with Python, after concat some sample DFs as below:</p>
  
  <pre><code>import pandas as pd
  
  df_list = []
  
  df_0 = pd.DataFrame('1.11', index=['SS_0'], columns=['Tx-UDP'])
  df_1 = pd.DataFrame('2.22', index=['SS_1'], columns=['Tx-UDP'])
  df_2 = pd.DataFrame('3.33', index=['SS_1'], columns=['Tx-TCP'])
  
  df_list.append(df_0)
  df_list.append(df_1)
  df_list.append(df_2)
  
  df_final = pd.concat(df_list) # type: pd.DataFrame
  
  print(df_final)
  </code></pre>
  
  <p>I got results print out as:</p>
  
  <pre><code>     Tx-TCP Tx-UDP
  SS_0    NaN   1.11
  SS_1    NaN   2.22
  SS_1   3.33    NaN
  </code></pre>
  
  <p>But what I really want the result is like below format, which based on index content, if index content are the same, the value will be put into same row under each columns, rather than starting a new row and fill in with NaN, i.e. index 'SS_1' in example. If index is unique and no data presenting under certain column, then fill in with 'NaN' is fine, i.e. index 'SS_0'/col 'Tx-TCP'.</p>
  
  <pre><code>     Tx-TCP Tx-UDP
  SS_0    NaN   1.11
  SS_1   3.33   2.22
  </code></pre>
  
  <p>Tried with concat/merge/join/grouby etc., but haven't found a way to do that. 
  Please help to advise and Thanks a lot in advance!</p>