In ma previous post, Creating Jump Plot, we used Bézier function for drawing the curves. But Bézier curve is not the sole option.

Today, we would like to show you how to use the familiar Sine function and Triangular function for drawing those curves. I got the inspiration from a viz of Sebastián Soto Vera. Check it out, it is a great use case of jump plot.

We will use the same data set as in my last post. To make it simple, we will only focus on contiguous sequences, which go through all the check points. This will make the calculations a lot simpler.

Introduction

Jump Plot is used in visualizing process measurement.

In my research regarding Bézier curve, I finally got a chance to have a closer look at Chris DeMartini's masterful vizzes. By taking apart his jump plots, I found something strange. I couldn't understand the data structure initially.

I realized eventually that he transformed the data set in order to use piece-wise Bézier curves so that he can create jump plots. This almost doubled the size of the data set.

The other day, Rajeev Pandey asked me a question regarding the calculation in his dashboard privately. I didn't have time to look into it. Fortunately the gracious Simon Runc found that the issue was in data densification.

Rajeev is trying to replicate a viz by Zen Master Rody Zachovich, which seems to be inspired by a viz of Cody Crouch.

I spent some time looking into both the vizzies. I found a few computational solutions which may be interesting to share.

How to chart user growth? Sounds like a simple question. Yet I got asked a number of times on the topic. It may not be as straightforward as one might have thought. Seems no one is documenting it. So I decided to write it down.

What is user growth?

- it is not the count of active users per month/week/day and the accumulation thereof.

- it is the accumulation of unique users along time.

It takes 3 steps to do it.

Ups and downs are the simplest indicators of trends. They are so simple that they may entice people to look further into the data. Just want to emphasize they are simple but important to data visualization.

The one and only Rody Zachovich created a great dashboard on World Economical Freedom Indicator in the MakeoverMonday Week9 project. As always, his dashboard is crisp and full of creativity.

Usually a #MakeoverMonday project is supposed to be done in a couple of hours.

Chris Mc on Twitter is kind of amazed that a rather sophisticated graph like Julia Set can be generated using only 8 rows of data.

OMG EIGHT rows of data !!!! I've often thought of doing this, just never got around to trying.

— Chris Mc (@cmcau) March 2, 2018 I am going to show that we can reduce that to 2 rows.

In visualizing math functions, usually we can use a fairly small data set as seed, such as 2 rows for one dimensional graphs or 8 rows for 3 dimensional graphs.

The fractals are always fascinating. I am totally mesmerized by it. Inspired by Zen Master Noah Salvaterra's work, here I created the Julia set using Tableau alone for both generating all the data marks and visualizing them, without using external tools like Python or R.

Julia set is the original fractals that inspired Mandelbrot to found his own set. Mandelbrot set is a subset of Julia set.
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