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Category: Visualization

Visualizing a SQL Server Kubernetes Statefulset

Published 2025-02-07 by Kevin Feasel

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

Published 2025-02-04 by Kevin Feasel

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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Choosing the Right Power BI Canvas

Published 2025-02-04 by Kevin Feasel

Elena Drakulevska shares some advice:

The same goes for your Power BI report—get the size wrong, and your users will struggle with cluttered visuals, excessive scrolling, or awkward gaps. Or worse, you’ll create a report that looks amazing on your screen but completely breaks when someone else opens it.

Trust me, I’ve seen it—an ultrawide masterpiece designed for the boss’s fancy monitor… except no one else at the company had that monitor.

Yeah, this brings back memories, though in my case, it was that the developers (including me) had wide-screen monitors in 1080p and the people using our product had standard resolutions like 1280×1024 or even 1024×768.

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Building Flowcharts in R

Published 2025-01-20 by Kevin Feasel

Pau Satorra makes a chart:

Fortunately, there are several packages in R for drawing flowcharts using different approaches. The problem is that the programming is generally quite complex, and the numbers have to be entered manually or parameterized beforehand. These flowcharts can have reproducible problems because if data changes, we have to manually change the parameters again.

To make our lives easier, there’s a new {flowchart} package that uses the tidyverse workflow, which allows to create many different types of flowcharts in just a few steps.

Read on to learn more about the package. I originally thought it was based on mermaid.js based on the way the final product looked, but a quick code review has disabused me of the notion. H/T R-Bloggers.

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Porting an R Shiny App to Observable Framework

Published 2025-01-17 by Kevin Feasel

Tim Brock makes a change:

If you’re interested in interactive data visualisation you’ve probably heard of the d3 JavaScript library, even if you’ve never used it or even know any JavaScript. Mike Bostock, the creator of d3, and colleagues followed this up with d3.express, which was quickly renamed to Observable.

Read on to see how you can build a simple Observable Framework app without spending a lot of time troubleshooting JavaScript code.

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Near Real-Time Data Plotting in Python

Published 2025-01-16 by Kevin Feasel

Hristo Hristov wants to know where the International Space Station is:

Gathering data on events as they occur in real-time is a powerful and popular technique in scientific and industrial computing. If we can query an online REST API representing the position of the International Space Station’s (ISS), how can we visualize these data in real time? How do you plot the data points as soon as they arrive and observe changes in the station’s position immediately? Let’s look at using Python for a real time plot of data.

Click through for the solution and plenty of explanation along the way.

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Re-Using Visual Formatting between Power BI Reports

Published 2024-12-17 by Kevin Feasel

Kurt Buhler does a bit of recycling:

If you build Power BI reports, then you know how much time it costs to format visuals so that they work and look the way that you want them to. This applies not only when you make new reports, but also when you need to maintain or make changes to existing ones. When a report gets fancy in its design (sometimes unnecessarily so, if we are frank), then, often, this is accompanied by a need for many formatting tweaks and changes. Inevitably, this formatting becomes time consuming (and sometimes frustrating) to deal with when there is a problem to fix or a modification to make. How can we make formatting and maintaining Power BI reports both more convenient and more efficient?

Read on for the answer.

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Data Visualization in Matplotlib

Published 2024-11-26 by Kevin Feasel

Rajendra Gupta generates some graphics:

Data analysis requires analysts to handle structured, semi-structured, or unstructured data. Small datasets with few rows and columns are easy to understand. However, as the data complexity increases with many interlinked variables, getting data insights from tabular formatted data becomes challenging. According to a recent study from MIT, the human brain processes an entire image in just 13 milliseconds. Therefore, it is helpful to learn Python and visualization together.

How do we use Python to generate plots from the data to analyze patterns, correlations, and trends? What plots are available, and how do we use them with customizations? Let’s explore them in this tip.

There are a few visualization libraries in Python I prefer over matplotlib, and for static graphics, ggplot2 in R has pretty much everything else beat. But matplotlib is essentially the standard, so it’s important to know.

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Building a Gantt Chart

Published 2024-11-26 by Kevin Feasel

Amy Esselman wants to know if you’re on time or have any slack:

A Gantt chart is used to visually present tasks or events over time. It consists of a horizontal axis of time and horizontal bars representing the duration of each item arranged along the vertical axis.

The visual was popularized in the early 1900s by American engineer and management consultant Henry Gantt, for whom the chart is named. Most commonly, this view is used to see the start date and duration of each task in a larger project to better understand timelines, milestones, and dependencies.

Click through for an overview of the chart, where it can be useful, and some of the limitations of the chart.

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