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The Data School Week Two

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Let’s create radial chart !!!

The sample will use U.S international travel

  1. Union the dataset and create the calculation filed

    name “path Order” -> IIF([Table Name] = “Dataset US international travel.csv”, 0, 1)
    drop “path order” from measure to tables
  2. Create Parameters, “Radial inner (0.7)” and “Radial outer(1)”
  3. Create “Radial Field” [Departures] -> ‘’scheduled”+”chartered”
  4. Create “Radial Angle” -> (INDEX()-1)*(1/WINDOW_COUNT(COUNT([Radial Field])))*2*PI()
  5. Radial Normalised Length -> [Radial inner]+ IIF(ATTR([path Order]) = 0, 0, SUM([Radial Field])/WINDOW_MAX(SUM([Radial Field]))*([Radial outer]-[Radial inner]))
  6. Radial X -> [Radial Normalised Length]*COS([Radial Angle]) -> computing to “Date”
  7. Radial Y -> [Radial Normalised Length]* SIN([Radial Angle]) -> computing to “Date”
  8. Drop Radial Y and X to column and row
    Measure_flight to colour
    Date to detail
    path Order to Path

  9. Then you will get very beautiful radial chart 🙂

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