title: Merge two pandas dataframes with timeseries index
body: <p>I have two pandas dataframes that I would like to merge/join together</p>
  
  <p>For example:</p>
  
  <pre><code>#required packages
  import os
  import pandas as pd
  import numpy as np
  import datetime as dt
  
  # create sample time series
  dates1 = pd.date_range('1/1/2000', periods=4, freq='10min')
  dates2 = dates1
  column_names = ['A','B','C']
  df1 = pd.DataFrame(np.random.randn(4, 3), index=dates1, 
  columns=column_names)
  df2 = pd.DataFrame(np.random.randn(4, 3), index=dates2, 
  columns=column_names)
  
  df3 = df1.merge(df2, how='outer', left_index=True, right_index=True, suffixes=('_x', '_y'))
  </code></pre>
  
  <p>From here I would like to merge the two datasets in the following manner(Note the order of columns):</p>
  
  <pre><code>                                              A_x       A_y       B_x       B_y       C_x       C_y
  2000-01-01 00:00:00 2000-01-01 00:00:00 -0.572616 -0.867554 -0.382594  1.866238 -0.756318  0.564087
  2000-01-01 00:10:00 2000-01-01 00:10:00 -0.814776 -0.458378  1.011491  0.196498 -0.523433 -0.296989
  2000-01-01 00:20:00 2000-01-01 00:20:00 -0.617766  0.081141  1.405145 -1.183592  0.400720 -0.872507
  2000-01-01 00:30:00 2000-01-01 00:30:00  1.083721  0.137422 -1.013840 -1.610531 -1.258841  0.142301
  </code></pre>
  
  <p>I would like to preserve both dataframe indexes by either creating a multi-index dataframe or creating a column for the second index. Would it be easier to use merge_ordered instead of merge or join?</p>
  
  <p>Any help is appreciated.</p>