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Category: Visualization

Alternative Ways of Displaying Heatmap Data

Cole Nussbaumer Knaflic gives us a couple alternatives to displaying data in a heatmap:

I often describe heatmaps as a good means for getting an initial view of your data. They can help you start to explore and understand where there might be something interesting to highlight or dig into. But once you’ve identified the noteworthy aspects of your data, should you use heatmaps to communicate them?

As often is the case, it depends.

If you are communicating to an audience who likes to see data in tables—applying heatmap formatting can provide a visual sense of the numbers without fully changing the approach (or having it feel like you’ve taken detail away). If you know your stakeholders will want to look up specific numbers (particularly in the case where different stakeholders will care about different numbers) and then understand them in the context of the broader landscape, a heatmap may also work in this scenario.

Click through for some ideas.

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Changing Power BI Slicer Appearance

Prathy Kamasani has a video:

In my recent open data project, I created a single page report model with a sparse slicer. It’s a good trick for anyone who wants to make their slicer look a bit sleeker. Like any other visual in Power BI, Slicers also have many properties. By default, below is how slicer looks in Power BI, but I made few changes to make it look like the one on left, in a few steps.

Click through for the video.

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Xenographs

Alex Velez talks about xenographs:

I recall the first time I came across a horizon chart. Two thoughts came to mind: 1) this looks cool; and 2) I don’t have the energy to figure this out. Fast forward to now. I’ve learned how to read horizon charts, and I’ve even identified a few good use cases for them. This illustrates both the problem and the potential of xenographs. Let’s explore the potentially problematic side first.

Novel approaches to visualizing data can intimidate audiences. They introduce a learning curve because a never-before-seen graph typically requires time and energy to decipher. This obstacle could be enough to dissuade audiences from consuming the data altogether. Even if your audience does invest their time, the resulting conversation is often about reading the visual instead of the primary takeaway. This seems counterintuitive, especially in the explanatory analytics space, but it doesn’t mean we should denounce everything novel.

My response to this depends heavily on the medium. If you’re giving a presentation, a novel or underused chart can be good if it helps tell the story. You have the advantage of being there to explain the dynamics of the diagram for people who have never seen it before. For an informative article, you have some ability to elaborate, as in this bracket win probabilities diagram, which is exactly the type of thing you’d see in certain newspapers and magazines. But unless your visual is immediately intuitive (and I’d consider things like a Manhattan plot or maybe a Dot-boxplot to be intuitive enough for most audiences), I don’t think I would include many of those on public-facing or corporate dashboards, as they’re liable to confuse people and you might not have the space available to explain how this works.

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Using Tables for Visualization

Alex Velez takes us through one of the simplest visuals:

Tables are a common way to show data, but in my current work, I don’t create them frequently. Admittedly, when I come across a table, I often choose to visualize the data. I should clarify that I am not proposing that we never build tables. Instead, let’s understand their benefits and shortcomings so we can be thoughtful about when to use them and how to design good data tables.

Click through for some interesting thoughts around a sometimes-forgotten visual.

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Visualizing Seinfeld

Andy Kirk walks through a brand new book:

This project is a compilation of visual analysis I’ve been working on for a couple of years to pursue a curiosity I had about the rhythm and texture of Seinfeld, looking into how it was written and how it was produced.

The musicality of language is something defines the signature comedic talent of Jerry Seinfeld and, co-creator, Larry David. Like music, situation comedy has rhythm and it has texture. The rhythm is shaped by its temporal structures and pacing; textures are formed from the arrangements of characters and locations which amalgamate into the comedy. All orchestrated by the storylines and dialogue emerging from the writers.

It is an exploration of the show’s musicality that forms the purpose of this book. It presents a portfolio of visuals produced, intended for people who share my Seinfeld fanaticism. It is a body of work akin to giving the show something of a sports analytics treatment, investigating how Seinfeld and David utilised their resources – the people, places, and the dialogue – to translate their creativity from the page and onto our screens.

It’s an interesting look at the show and there will be a limited run on physical copies of the book.

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ggwebthemes as a Package

Petr Baranovskiy has released an R package:

I was happy to see that some people liked those and suggested that I should make a package. I tended to view packages as large collections of code and functions, but as Sébastien Rochette wisely put it, “If you have one function, create a package! If this simplifies your life, why not?” And since I will be frequently using these themes in subsequent posts, I’d like to make it as convenient as possible for the reader to install and use them.

So here is the ggwebthemes package! It has the same three themes, which I have tweaked and improved some more.

Click through for instructions on how to install ggwebthemes via GitLab.

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Power BI Fonts and Dyslexia

David Eldersveld has some tips to make it easier to read your dashboards:

Power BI font selection is currently limited to about two dozen choices. These include a mix of serif versus sans serif, monospaced versus not monospaced, bold versus light, and more. While I do not have a definitive list of specific fonts–and I would love additional input from readers who live with dyslexia–there are some preferred font choices as well as choices to avoid when designing Power BI reports.

Click through for good recommendations regardless of whether any of your dashboard viewers are dyslexic.

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Calculating Color Contrast

Meagan Longoria has a new Power BI report for us:

Color contrast (as calculated in the WCAG 2.1 success criteria) is dependent on luminance. Luminance is the relative brightness of any point in a color space, normalized to 0 for darkest black and 1 for lightest white. In order to calculate color contrast you must first get the luminance of each color.

As an example, I have colors #F3F2F1 and #007E97. In this hex notation, often explained as #RRGGBB, the first two digits represent red, the second two digits are green, and the last two digits are blue. Each two digits is a value that represents the decimal numbers 0 to 255 in hexadecimal notation. The same red, green, and blue values can be represented in decimal notation as integers, and this is what is used to calculate luminance. #F3F2F1 is RGB(243, 242, 241), and #007E97 is RGB(0,126,151).

Read the whole thing, check out the report, and test those color contrast values.

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Displaying Map Routes with Power BI

Chris Webb lays out map routes:

In last week’s post I described the new Power Query M functions for working with Well Known Text objects, and in a post a few weeks ago I showed how you can use the Icon Map custom visual to display Well Known Text data. In this post I’ll show you how you can put all this together to do something really useful: display routes on a map in a Power BI report.

First of all you’ll need to download the latest version of the Icon Map custom visual here, because at the time of writing the version in AppSource doesn’t have the WKT functionality needed. Second, you’ll need a data source with a table of latitudes and longitudes that represent points on a route that you want to plot. I’m going to use the Azure Maps Get Route Directions API as my data source; to keep things simple I’m going to use the Shared Key authentication method for this API, but I’ll explain below why this can be a problem in the real world. To follow the example you’ll need to create an Azure Maps Account in the Azure Portal so you can get your own key.

Read on for an interesting demo.

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