I am a big fan of step lines (here is a good example from datasketch.es) so I was really excited to see that line type announced at last year’s Devs on Stage. While we wait for that feature to be provided directly within the product, we have two choices: (1) don’t use them, or (2) build them ourselves. Choice two is much more the DataBlick way, so I have tried to provide you with a few steps that you can follow to build this chart type yourself. You can also take a look at Tim Ngwena’s post here which details another method that you can look into for your use case.
Step lines are just lines at the end of the day. When I started looking into how to plot their points accordingly, the prep work reminded me quite a bit of the data prep needed for Jump Plot. We basically need to take our list of points and add an additional mark for each point, and potentially one at the origin (0,0) if that is desired for our viz (as it was in this case). I will be using step lines to help analyze the scoring to par across PGA tournaments this year.
Here is a small sample of the data we will be working with going forward, this is an aggregated data set, looking at the average score to par for pros on the PGA tour this year. We are going to plot “hole” on the x-axis and “Avg Score” on the y-axis to make our viz.Read More