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Category: Visualization

Creating a Dashboard in Snowflake

Kevin Wilkie doesn’t just do e-mails:

If you haven’t had a chance to mess around in Snowflake, there are internal dashboards that you can provide to your users (or just use yourself) so that you can get the latest data.

Today, I want to quickly show a use case for these Dashboards and one way that you can get data quickly and easily in a nice format.

And right above Dashboards is Streamlit, one of my favorite libraries for building rapid application prototypes and even small data applications.

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choroplethr 4.0.0 Now in CRAN

Ari Lamstein has an announcement:

With this version, I have transferred the maintenance of choroplethr to Zhaochen He, an economics professor at Christopher Newport University. Zhao addressed the issues that led to choroplethr being archived from CRAN in February. Please join me in thanking Zhao for his contribution!

Click through for the updates, as well as what Ari views as the current challenges for the project as he hands the project over Zhaochen He. H/T R-Bloggers.

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Reactable Tables with Sparklines in Shiny Apps

Osheen MacOscar continues a series:

This is the third blog in a series about the {sparkline} R package for inline data visualisations. You can read the first one about getting started with the package here and the second one about embedding them in HTML tables with the {reactable} package here.

In this blog I am taking it a step further and demonstrating how to use our sparkline reactable table in a Shiny app. Thankfully {reactable} has some helpful functions that make this super easy! I will also look at using a dynamic traffic light image in a reactable table at the end.

Click through to see how it all works.

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Thoughts on Dark Mode Reports in Power BI

Elena Drakulevska reminds us to think of the user:

Lately, there’s been a lot of hype around dark-mode reports—especially now that dark mode is officially a thing in Power BI. It’s sleek, it’s trendy, and, let’s be honest, it looks pretty cool.

But before we all jump on the dark-mode train, let’s pause for a second. Because, like most things in design, IT DEPENDS.

Click through for a primer on accessibility. Meanwhile, my hottest design take is that dark mode is wildly overrated. Invest in proper task lighting.

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Building a Top N Analysis in Power BI

Hamza Boubou builds a dynamic report:

There was a requirement from my client that seemed simple at first but turned out to be a Trojan horse after deeper investigation. The goal was to create a Power BI Time Comparisons Top N Analysis page, giving users complete control over the Top/Bottom N products based on multiple metrics. Users needed to define the period, compare it with other periods, and adjust the N parameter dynamically.

Read on to see how Hamza was able to solve this customer request.

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Conditional Formatting via Power BI Visual Calculation

Marco Russo and Alberto Ferrari talk highlighting:

However, visual calculations are incredibly convenient when it comes to calculations that are specifically tied to a visual. Let us face it: every semantic model contains measures with intricate ISINSCOPEHASONEVALUE, and SELECTEDVALUE function calls whose only goal is to determine the color of a font or the background of a cell. An example of the intricacy of those measures is in one of our most viewed articles here: https://www.sqlbi.com/articles/filtering-the-top-products-alongside-the-other-products-in-power-bi/.

Visual calculations can be used to control conditional formatting starting with the February 2025 version of Power BI. Several small details must be known to use them, but they are definitely worth learning.

Read on to see how it works. Conditional formatting has always seemed to be oddly difficult to do in Power BI. If you were in the happy path for conditional formatting, it’s a few mouse clicks. But if not, then good luck.

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Building Sparklines in R Shiny

Osheen MacOscar needs a series of tiny visuals:

All of the plots from this package use the sparkline function, and we pass the type of chart we want as the type argument (default is line). The function will take a vector or list for the values argument, depending on the type of chart we are creating this can be either data to plot or specifications for the plot.

Click through for a list of the sparkline-esque visuals you can create as well as how you can use the sparkline package and some examples of outputs.

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Visualizing a SQL Server Kubernetes Statefulset

Andrew Pruski builds a diagram:

The other day I came across an interesting repo on github, KubeDiagrams.

What this repo does is generate Kubernetes architecture diagrams from Kubernetes manifest files…nice!

Deploying applications to Kubernetes can get complicated fast…especially with stateful applications such as SQL Server.

So having the ability to easily generate diagrams is really helpful…because we all should be documenting everything, right?

Click through for instructions and a couple of gotchas Andrew ran into along the way.

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Alternatives to Error Bars

Alex Velez admits to error:

During a client workshop, someone asked me if I was a fan of error bars and whether they should use them in their presentations. As I readied my standard “it depends” response, I realized that for once, it didn’t depend. I couldn’t think of a single time when error bars would be the ideal solution for communicating data. (For clarity, if they had asked whether they should articulate the margin of error around their data, my answer would have certainly been it depends. I just wouldn’t use error bars to do so.)

Before I discuss why I’m not a fan of error bars and an alternative solution, let’s explore what they are. 

Click through for Alex’s thoughts, including a pair of interesting alternative displays.

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