title: Read lists into columns of pandas DataFrame
body: <p>I want to load lists into columns of a pandas DataFrame but cannot seem to do this simply.  This is an example of what I want using <code>transpose()</code> but I would think that is unnecessary:</p>
  
  <pre><code>In [1]: import numpy as np
  In [2]: import pandas as pd
  In [3]: x = np.linspace(0,np.pi,10)
  In [4]: y = np.sin(x)
  In [5]: data = pd.DataFrame(data=[x,y]).transpose()
  In [6]: data.columns = ['x', 'sin(x)']
  In [7]: data
  Out[7]: 
            x        sin(x)
  0  0.000000  0.000000e+00
  1  0.349066  3.420201e-01
  2  0.698132  6.427876e-01
  3  1.047198  8.660254e-01
  4  1.396263  9.848078e-01
  5  1.745329  9.848078e-01
  6  2.094395  8.660254e-01
  7  2.443461  6.427876e-01
  8  2.792527  3.420201e-01
  9  3.141593  1.224647e-16
  
  [10 rows x 2 columns]
  </code></pre>
  
  <p>Is there a way to directly load each list into a column to eliminate the transpose and insert the column labels when creating the DataFrame?</p>