title: Pandas concat DataFrames - keep original order of index
body: <p>I am trying to concat two dataframes:</p>
  
  <pre><code>df2:
  CU  Pmt  2017-02-01
  h    b        15
  h    d        12
  h    a        13
  </code></pre>
  
  <p>and df1:</p>
  
  <pre><code>CU  Pmt  'Total/Max/Min'
  h    b        20
  h    d        23 
  h    a        22
  a    b        16
  a    d        13
  a    a        14
  </code></pre>
  
  <p>such that df3:</p>
  
  <pre><code>CU  Pmt  2017-02-01  2017-02-02
  h    b      15           20
  h    d      12           23
  h    a      13           22
  a    b      NaN          16
  a    d      NaN          13
  a    a      Nan          14
  </code></pre>
  
  <p>I am using a multi index of index_col = [0,1] for both</p>
  
  <p>This is what I have: </p>
  
  <pre><code>date = '2017-02-02'
  df1 = pd.read_csv(r'Data\2017-02\2017-02-02\Aggregated\Aggregated_Daily_All.csv', usecols=['CU', 'Parameters', 'Total/Max/Min'], index_col =[0,1])
  df1 = df1.rename(columns = {'Total/Max/Min':date})
  
  df2 = pd.read_csv(r'Data\2017-02\MonthlyData\February2017.csv', index_col = [0,1])
  df3  = pd.concat([df2, df1], axis=1)
  df3.to_csv(r'Data\2017-02\MonthlyData\February2017.csv')
  </code></pre>
  
  <p>However, df3 is coming out as:</p>
  
  <pre><code>CU  Pmt  2017-02-01  2017-02-02
  a    a      NaN          14
  a    b      NaN          16
  a    d      Nan          13
  h    a      13           22
  h    b      15           20
  h    d      12           23
  </code></pre>
  
  <p>Which has <code>CU</code> and <code>Pmt</code> (the two index columns) in alphabetical order. How is it possible to keep the original order, so that for all new indexes added for a new date, they are added at the bottom?</p>