The Step() is like Interpolate() except that it finds the corresponding y for a given x from a step-function fit rather than a linear fit. Use Step() with discrete y values (that is, when the y value’s corresponding x value can be only y1 or y2). However, when the y value’s corresponding x value can fall between y1 and y2, use Interpolate().
As with Interpolate, the data points can be specified as a list:
If the discounts were on a sliding scale (in this example, between 5 and 10, you would use Interpolate():
As with Interpolate(), the data points must create a positive slope.