title: Fit a small DataFrame with a simple function
body: <p>I have a set of a lot of Dataframes with the following shape:</p>
  
  <pre><code>dat = pd.DataFrame({'Y':[0.0455,0.079,0.059,0.144],'X':[0.055,0.110,0.165,0.220]})
  
  `dat
  Out[14]: 
          Y      X
      0  0.0455  0.055
      1  0.0790  0.110
      2  0.0590  0.165
      3  0.1440  0.220
  </code></pre>
  
  <p>I'm trying to fit this data with a function: Y = kX**m
  My expected output is to get parameters 'k' and 'm'</p>
  
  <p>Seems that is not a hard job to do, but I only find some examples using 'scipy.optimize.curve_fit' that requieres several rounds of simulation to fit the data and I think is too complicated only for a few numbers.
  Some ideas?</p>
  
  <p>CLUE: Using a commercial software I already know that
  k = -0.3176
  m = 0.8935</p>
  
  <p>Thanks in advance</p>