title: Creating a 3D SMOOTH surface plot from pandas dataframe
body: <p>I have a dataframe <code>z1</code> with entries as follows:</p>
  
  <pre><code>z1.ix[1:10,1:3]
              2017-04-01  2017-05-01
  2017-01-04         NaN    0.993549
  2017-01-05         NaN         NaN
  2017-01-06    0.830973    0.978463
  2017-01-09    0.926456         NaN
  2017-01-10    0.998371    0.997590
  2017-01-11    0.997539    0.999364
  2017-01-12    NaN         0.989801
  2017-01-13    0.999701    0.998526
  2017-01-16    0.995119    0.998891
  </code></pre>
  
  <p>I am trying to create the surface plot using the row index as X-axis, column names as Y-axis and values on Z-axis.</p>
  
  <p>I tried the following:</p>
  
  <pre><code>    import matplotlib as mpl
      import matplotlib.pyplot as plt
      from mpl_toolkits.mplot3d import Axes3D
  
      x = z1.columns
      y = z1.index
      X, Y = np.meshgrid(x, y)
      Z = z1
      fig = plt.figure()
      ax = fig.add_subplot(111, projection='3d')
      ax.plot_surface(X, Y, Z)
  </code></pre>
  
  <p>I get following error:</p>
  
  <pre><code>TypeError: ufunc multiply cannot use operands with types dtype('float64') and dtype('&lt;M8[ns]')
  </code></pre>
  
  <p>Both the column names and row index for my dataframe are datetimes. How can I improve my code to make the 3D SMOOTH surface plot.</p>
  
  <pre><code>z1.shape
  (182, 32)
  </code></pre>