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Category: Visualization

Custom Power BI Visuals with Charticulator

Published 2019-12-06 by Kevin Feasel

Kasper de Jonge shows how we can use Charticulator to build out custom visuals in Power BI:

Recently I attended an excellent session by Andy Kirk on the state of data visualization for 2019. One of the tools Andy is most excited about is called Charticulator. For those of you that haven’t heard about it, Charticulator is an open source project from Microsoft Research. Using a web UI you can design almost any charts by interactively specifying constraints (NO code).

The best news is that you can use these visuals directly in Power BI. You can even use your own data coming from the PBI data model. This came as news for many at Andy Kirk’s session so decided to do a quick post on it. Building very custom charts entices a lot of data artists but it is often hard to bring this to main stream BI product. The ease of the Charticulator and Power BI integration brings this type of data visualizations to a much broader audience.

This is a lot easier than telling people to learn D3, though Charticulator will necessarily have more limitations than writing all of the code yourself.

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Realistic-Looking Islands with R

Published 2019-12-04 by Kevin Feasel

Holger K. von Jouanne-Diedrich uses fractal math to create realistic-looking artificial islands:

Here we will turn this principle on its head and use it to actually create realistic-looking landmasses with R. The inspiration for this came from chapter 4 “Infinite Detail” of the book “Math Bytes” by my colleague Professor T. Chartier from Davidson College in North Carolina.

The idea is to start with some very simple form, like a square, and add more detail step-by-step. Concretely, we go through every midpoint of our ever more complex polygon and shift it by a random amount. Because the polygon will be getting more and more intricate we have to adjust the absolute amount by which we shift the respective midpoints. 

Click through for the code.

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Using PowerPoint to Create Power BI Layouts

Published 2019-12-03 by Kevin Feasel

Jon Fletcher has a good tip for snazzing up a Power BI dashboard:

First question, why bother with layouts?
Using layouts in Power BI allows a user to make their visuals stand out better, the page looks professional and more appealing to its audience.

Second question, why PowerPoint?
The default page size in Power BI desktop is 16:9, (this trick doesn’t work for other Power BI page sizes), which is identical to a PowerPoint slide.
Therefore whatever is designed in PowerPoint will fit onto a Power BI page perfectly. Also PowerPoint is very easy to use; most people are familiar with it.

Click through for an example. It’s easy to go overboard with this, but Jon does a good job of using a muted color so that the edges don’t overwhelm your eyes. I might knock it down a shade or two further from that, but regardless, this is a nice tip.

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United States Maps in R

Published 2019-12-02 by Kevin Feasel

Laura Ellis shows how to use the usmap package in R:

Today, I’d like to share the package ‘usmap’ which enables incredibly easy and fast creation of US maps in R.

In honor of US Thanksgiving tomorrow, I’m going to make this blog Thanksgiving themed! In this tutorial, we will use the gTrendsR package to pull US Google search results on the keyword “thanksgiving” and plot the popularity by state.

Click through for that demo, as well as links to more demos on map usage.

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Visualizing Kafka Data Using D3

Published 2019-11-27 by Kevin Feasel

Mihalis Tsoukalos extracts, explores, and visualizes data (with D3) from a Kafka topic:

Now that you have your data in JSON format, you will use D3.js in order to visualize it. As JavaScript code is embedded in HTML files, the final version of the D3.js code can be found in visualize-spatial.html, which contains the following code:

D3 is extremely powerful, though that power comes with a fairly steep learning curve.

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Fun With Waffle Plots

Published 2019-11-25 by Kevin Feasel

Sebastian Sauer has a two-parter on waffle plots. The first part is an introduction:

A waffle diagram is a variant of (stacked) bar plots or pie plots. They do not have great perceptual properties, I’d suspect, but for some purposes they may be adequate. This is best explored by example. This post draws heavily from the introduction of hrbrmstr to his Waffle package.

The second part uses emojifont to show pictograms as well:

A Pictogram may be defined as a (statistical) diagram using icons or similar “iconic” graphics to illstrate stuff. The waffle plot (see this post) is a nice object where to combine waffle and pictorgrams. Originally, this post was inspired by HRBRMSTR waffle package, see this post, but I could not get it running.

Maybe the easiest way is to work through an example (spoiler: see below for what we’re heading at).

This type of plot doesn’t work for everything, but I can think of a few places where it’d be the right choice.

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Decomposition Trees in Power BI

Published 2019-11-22 by Kevin Feasel

Tomaz Kastrun takes us through a new visual in Power BI:

Decomposition tree is a data presentation of slicing and dicing of selected metrics based on the attributes of these metrics or with combination of other metrics. Another great aspect of this visual is to analyze the selected variable with many metrics or attributes (dimensions) as the same time.

It’s not the type of visual I’d want to see on a dashboard, but I can see it as quite useful in exploratory data analysis.

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Visualizing a Table

Published 2019-11-01 by Kevin Feasel

Cole Nussbaumer Knaflic takes a fairly simple table and creates eight visuals out of it:

STEP 1: When I encounter this table, I start reading and scanning down columns and across rows. In terms of specific observations, I might start by noticing that the majority of accounts are in Tiers B and C, while Tiers A and A+—though they don’t make up a huge number (or percentage) of accounts—do make up a meaningful amount of revenue. In terms of questions, I wonder if the tiers are in order: I would think A+ belongs above A and am confused that they don’t appear that way in the table (perhaps due to alphabetical sorting?).

This is a really nice practical exercise if you want to learn how to apply the right visuals to tell your story.

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Plotting Three-Dimensional Linear Models

Published 2019-10-29 by Kevin Feasel

Sebastian Sauer shows a few techniques for visualizing linear models with two predictors:

Linear models are a standard way of predicting or explaining some data. Visualizing data is not only of didactical value but provides heuristical value too, as demonstrated by Anscombe’s Quartet.

Visualizing linear models in 2D is straightforward, but visualizing linear models with more than one predictor is much less so. The aim of this post is to demonstrate some ways do visualize linear models with more than one predictor, using popular R packages. We will focus on 3D examples, that is, two predictors.

I have a strong bias against 3D visuals because they tend to be so difficult to see clearly. There are times when they’re necessary, though.

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