title: Order of spline interpolation for pandas dataframe
body: <p>I have the following dataframe which shows data from Motion Capture, where each column is a marker (i.e. position data) and rows are time:</p>
  <pre><code>        LTHMB X RTHMB X
  0       932.109 872.921
  1       934.605 873.798
  2       932.383 873.998
  3       940.946 875.609
  4       941.549 875.875
  ...     ...     ...
  14765   NaN 602.700
  14766   562.350 NaN
  14767   562.394 NaN
  14768   562.421 NaN
  14769   562.490 602.705
  </code></pre>
  <p>In the data, there are some NaN values that I need to fill. I'm not really an expert in this so I'm not sure what is the best way to fill these.</p>
  <p>I know I can do forward/backward fill, and I also read about spline interpolation, which seems more sophisticated. In the documentation for <a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.interpolate.html#pandas.DataFrame.interpolate" rel="nofollow noreferrer">pandas.DataFrame.interpolate</a> it states that for spline you have to specify the order.</p>
  <p>What would I use for the order in this case? Each marker has an X, Y and Z. Does that mean I'd use a cubic spline, or is it not that simple?</p>