title: How to unpack the columns of a pandas DataFrame to multiple variables
body: <p>Lists or numpy arrays can be unpacked to multiple variables if the dimensions match. For a 3xN array, the following will work:</p>
  
  <pre><code>import numpy as np 
  a,b =          [[1,2,3],[4,5,6]]
  a,b = np.array([[1,2,3],[4,5,6]])
  # result: a=[1,2,3],   b=[4,5,6]
  </code></pre>
  
  <p>How can I achieve a similar behaviour for the columns of a pandas <code>DataFrame</code>? Extending the above example: </p>
  
  <pre><code>import pandas as pd 
  df = pd.DataFrame([[1,2,3],[4,5,6]])
  df.columns = ['A','B','C']    # Rename cols and
  df.index = ['i', 'ii']        # rows for clarity
  </code></pre>
  
  <p>The following does not work as expected:</p>
  
  <pre><code>a,b = df.T
  # result: a='i',   b='ii'
  a,b,c = df
  # result: a='A',   b='B',   c='C'
  </code></pre>
  
  <p>However, what I would like to get is the following:</p>
  
  <pre><code>a,b,c = unpack(df)
  result: a=df['A'], b=df['B'], c=df['C']
  </code></pre>
  
  <p>Is the function <code>unpack</code> already available in pandas? Or can it be mimicked in an easy way?</p>