title: python pandas, certain columns to rows
body: <p>I have a pandas dataframe, with 4 rows and 4 columns - here is asimple version:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  rows = np.arange(1, 4, 1)
  values = np.arange(1, 17).reshape(4,4)
  df = pd.DataFrame(values, index=rows, columns=['A', 'B', 'C', 'D'])
  </code></pre>
  
  <p>what I am trying to do is to convert this to a 2 * 8 dataframe, with B, C and D alligng for each array - so it would look like this:</p>
  
  <pre><code>1  2 
  1  3
  1  4
  5  6
  5  7
  5  8
  9  10
  9  11
  9  12
  13 14
  13 15
  13 16
  </code></pre>
  
  <p>reading on pandas documentation I tried this:</p>
  
  <pre><code>df1 = pd.pivot_table(df, rows = ['B', 'C', 'D'], cols = 'A')
  </code></pre>
  
  <p>but gives me an error that I cannot identify the source (ends with </p>
  
  <blockquote>
    <p>DataError: No numeric types to aggregate</p>
  </blockquote>
  
  <p>)</p>
  
  <p>following that I want to split the dataframe based on A values, but I think the .groupby command is probably going to take care of it</p>