Have a data series representing the cumulative flow of a medium, i.e. a monotonously increasing series of values. The measurements are taken at irregular points, not at fixed intervals. Build the approximation for the average rate of flow in a time interval via difference calculation : (y2 - y1) / (x2 -x1). Want to represent this in a bar chart. I.e., assume I have the rate of flow at irregular points, at point x2 the the value for the rate of flow is (y2 - y1) / (x2 - x1). If this was a step-before graph, the area under the graph would be the integral, corresponding to the absolute flow. Don’t want to use a step before graph, but represent the integral approximation by bars. With irregulalry spaced time intervals at which measurements were taken, I need bars of variable size or a way to normalize the data to have bars of equal size, calculated in a way that preserves the integral property.
Does Plotly meanwhile support bars of variable size?
If not, how to solve this? Augmenting / normalizing my data series would lose valuable information, - when a specific measurement had been created, which could not any longer be correlated to other data series. Using shapes to supplement missing bars in a sparsely populates graph appears very messy to get right.