title: Calculating the difference between values based on their date
body: <p>I have a dataframe that looks like this, where the "Date" is set as the index</p>
  
  <pre><code>            A B C D E
  Date  
  1999-01-01  1 2 3 4 5
  1999-01-02  1 2 3 4 5 
  1999-01-03  1 2 3 4 5 
  1999-01-04  1 2 3 4 5 
  </code></pre>
  
  <p>I'm trying to compare the percent difference between two pairs of dates. I think I can do the first bit:</p>
  
  <pre><code>start_1 = "1999-01-02"
  end_1 = "1999-01-03"
  
  start_2 = "1999-01-03"
  end_2 = "1999-01-04"
  
  Obs_1 = df.loc[end_1] / df.loc[start_1] -1
  Obs_2 = df.loc[end_2] / df.loc[start_2] -1
  </code></pre>
  
  <p>The output I get from - eg Obs_1 looks like this:</p>
  
  <pre><code>A    0.011197
  B    0.007933
  C    0.012850
  D    0.016678
  E    0.007330
  dtype: float64
  </code></pre>
  
  <p>I'm looking to build some correlations between Obs_1 and Obs_2.  I think I need to create a new dataframe  with the labels A-E as one column (or as the index), and then the data series from Obs_1 and Obs_2 as adjacent columns.</p>
  
  <p>But I'm struggling! I can't 'see' what Obs_1 and Obs_2 'are' - have I created a list? A series? How can I tell? What would be the best way of combining the two into a single dataframe...say df_1.</p>
  
  <p>I'm sure the answer is staring me in the face but I'm going mental trying to figure it out...and because I'm not quite sure what Obs_1 and Obs_2 'are', it's hard to search the SO archive to help me.</p>
  
  <p>Thanks in advance</p>