title: Calculate the rate of change of a parameter, with given x and y coordinates
body: <p>I have X and Y coordinates and a corresponding value for the parameter of the interest. I would like to get the rate of change of this parameter.</p>
  <p>Here is the data excerpt:</p>
  <pre><code>+-----------+------------+-----------+
  |     X     |     Y      | Parameter |
  +-----------+------------+-----------+
  | 503830.38 | 4443799.09 |     12.78 |
  | 503837.37 | 4443809.46 |     12.36 |
  | 503840.75 |  4443792.1 |      9.48 |
  | 503844.36 | 4443819.82 |     13.05 |
  | 503847.74 | 4443802.47 |      8.95 |
  | 503851.11 | 4443785.11 |      8.33 |
  | 503851.35 | 4443830.18 |     13.84 |
  | 503854.73 | 4443812.83 |      9.05 |
  |  503858.1 | 4443795.48 |      8.27 |
  | 503858.34 | 4443840.55 |     14.28 |
  | 503861.47 | 4443778.12 |      5.27 |
  | 503861.72 | 4443823.19 |      9.12 |
  | 503865.09 | 4443805.84 |      8.22 |
  | 503865.33 | 4443850.91 |     12.56 |
  | 503868.46 | 4443788.49 |      5.32 |
  +-----------+------------+-----------+
  </code></pre>
  <p>I have tried numpy.gradient (<code>np.gradient(np.array(df))</code>) function and created a plot for the full dataset, but I couldn't really understand what are tuples produced. The explanation of the function states that it creates the gradient with regards to all axes and gives an example for 2D. However, what I want is to be able to specify the direction of interest. For example, considering that the data is in geographical coordinates, I would like to define the direction of the parameter rate of change in the S or SE direction.</p>