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Category: Visualization

Choroplethr 3.6.4 on CRAN

Published 2020-08-03 by Kevin Feasel

Ari Lamstein announces that Choroplethr version 3.6.4 is now on CRAN:

Choroplethr v3.6.4 is now on CRAN. This is the first update to the package in two years, and was necessary because of a recent change to the tigris package, which choroplethr uses to make Census Tract maps. I also took this opportunity to add new example demographic data for Census Tracts.

Read on for a listing of the updates, examples, and a request from Ari to help keep the project up to date by finding a suitable sponsor. H/T R-Bloggers

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Slopegraphs in Action

Published 2020-07-28 by Kevin Feasel

Mike Cisneros takes us through slopegraphs:

When we use slopegraphs, we are trying to show one specific thing: is the value in the first column higher, lower, or the same as the value in the second column? That change is easy to see when we connect those values with lines, because the lines will slope up or down, in the direction of the change.

The steeper the slope, the bigger the change; and, if one thing is going up more dramatically than its neighbors, a slopegraph will make that easier to see than a traditional line graph would.

Mike has some examples of where slopegraphs make sense as well as cases when they don’t.

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Using the Azure Architecture Icons

Published 2020-07-28 by Kevin Feasel

Steve Jones tries out some of the Azure Architecture Icons:

The icons are svg, so while they work in PowerPoint, adding them to something like this post in OpenLiveWriter doesn’t work. However, I could make a quick diagram and capture an image of it.

Not great, but it shows I can put icons on a page with arrows.

Going one step further, I’ve been digging into Diagrams by mingrammer lately. With it, you use Python to generate diagrams, and there are quite a few Azure icons in there, as well as AWS, on-prem, etc.

Here’s a quick example of what you can do, taken from an upcoming talk of mine:

There are some limitations based on the underlying library, such as how you can’t connect cluster to cluster—meaning I can’t draw a line from “Logging” to “Storage\Logs”; I have to draw it from a particular element (Loki) to a particular element (Elasticsearch). In a lot of traditional reference architecture diagrams, though, that isn’t a problem.

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Building a Windows Terminal Theme

Published 2020-07-27 by Kevin Feasel

Chrissy LeMaire has a nice-looking Windows Terminal theme:

I was sooo excited when Microsoft first made the announcement but was disappointed when I found out I’d have to run a specific version of Windows and compile the app myself. Whaat? No way, too much work. Now, it’s more widely available, so I decided to jump in and try it out. I love it and even miss Windows Terminal when I develop PowerShell on my Mac.

So here’s the Theme I’m contributing, which is based off of my favorite VS Code Theme, 1984 Unbolded. I call it Retrowave.

I went with essentially a black-and-grey theme for cmd + PowerShell and a bit more color (but still grey background) for WSL, but that’s so I can create screenshots easily without having to worry about color contrast on the printed page.

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A Warning on Power BI Custom Visuals

Published 2020-07-16 by Kevin Feasel

Martin Schoombee gives us a warning around relying upon free custom visuals:

Before you get the impression that I’m against custom visuals, let me say this: I love custom visuals! I myself have used many custom visuals in the past and have been very quick to look for a custom visual when I couldn’t get something to display or work the way I needed it to in Power BI.

Custom visuals fill an important gap where the base product is not yet where it needs to be, and what better way for Microsoft to see what people need and where they need to invest more time from a visualization standpoint? It’s an awesome concept and I like it.

Unfortunately there are a few BUT’s to follow, but let me first tell you my story…

Read the whole thing. I like custom visuals a lot, but there are risks in a corporate world, and I don’t necessarily mean security.

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Drill-Down Tables in Cube.js

Published 2020-07-07 by Kevin Feasel

Artyom Keydunov shows off drill-down tables in Cube.js:

Since the release of drill down support in version 0.19.23, you can build interfaces to let users dive deeper into visualizations and data tables. The common use case for this feature is to let users click on a spike on the chart to find out what caused it, or to inspect a particular step of the funnel — who has converted and who has not.

In this blog post, I’ll show you how to define drill downs in the data schema and build an interface to let users explore the underlying chart’s data. If you’re just starting with Cube.js, I highly recommend beginning with this Cube.js 101 tutorial and then coming back here. Also, if you have any questions, don’t hesitate to ask them in our Slack community.

Click through for the demo, as well as links to the source code and an online example.

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Tips for Improving Power BI Dashboards

Published 2020-07-01 by Kevin Feasel

Tino Zishiri has a set of tips to design better-looking dashboards:

There are several reasons why you should design great looking dashboards. Here are a few;

– They make information more accessible – end users benefit from an intuitive design that makes insight easy to obtain so they can make informed decisions.
– They help convey your message – you’re in a better position to tell a coherent story. Applying design principles can also help accentuate your message. My colleague Kalina Ivanova has written an excellent series of blogs on Data Storytelling with Power BI.
– They encourage user adoption – if a report is useful to users and has a great look and feel then you’re winning.

In this blog, I’ll briefly cover the building blocks that make up a good Power BI dashboard. I then explore the stepping stones that will level up your dashboard and take it from good to great.

One area where I do have some disagreement is that the Z and F layouts are fine for text-heavy formats, but generally “text-heavy” and “dashboard” don’t go together very well. My preference is the notion of focal points (go about 3/4 of the way down, to the section entitled “Where We Look”), which works much better at describing eye behavior for image-heavy layouts. That aside, I like this post a lot.

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Data Visualization in R

Published 2020-06-19 by Kevin Feasel

Dan Fitton provides an introductory overview to several visualization tools in R:

The other way to communicate data with R is to produce an interactive dashboard or web application within R using Shiny. Whereas Markdown reports are most useful for explanatory analysis; Shiny, in my opinion, is useful for exploratory data analysis. This is when you want to display information for investigative purposes, allowing the user to gain greater familiarity by having the ability to interact with data, filter it, and dig deeper into the underlying details.

Shiny is incredibly flexible, providing the user the capability of turning their R code and objects, including tables, plots, and analysis, into a comprehensive and interactive web page or app, without requiring a fully-fledged web development skillset. Although there is a steep learning curve, the freedom and precision Shiny brings means that for the most part you are limited only by your skillset rather than the tool itself.

I’ve seen some really useful Shiny dashboards. Dan is right that there can be a lot of work put into getting them right, but if you do, the results can be outstanding.

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