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Category: Visualization

Accessibility Features in Power BI

Published 2024-04-08 by Kevin Feasel

Elena Drakulevska takes us through some of the accessibility features in Power BI:

As data professionals, we’re constantly striving to create reports that effectively communicate insights to our audience. Did you know that within Power BI, there are hidden accessibility features that can enhance the usability for all users—with minimal effort on your part? Today, we’re digging into this overlooked aspect of Power BI and exploring how these features can elevate your data visualization projects.

Click through for three features.

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The Power of the (Scatter) Plot

Published 2024-04-05 by Kevin Feasel

Kurt Buhler digs into scatter plots:

In many reports, it is common to find large tables or matrixes with a lot of information. Business users come to these reports to get the details they need to answer questions, make decisions, and take actions. However, these detailed tables can be inefficient, requiring users sort, drilldown, and filter them to find actionable data.

Consider the following example of a matrix to analyze gaps in year-over-year growth by product, and dissect those by region. In this scenario, the intended purpose of the report is for a sales team to analyze why we did not hit our revenue growth target.

Read on to learn what you can do with a scatter plot, either natively in Power BI or via custom visual.

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Tips for Dealing with Large Spatial Datasets

Published 2024-04-05 by Kevin Feasel

Rhian Davies consults the map:

I love playing with spatial data. Perhaps because I enjoy exploring the outdoors, or because I spend hours playing Geoguessr, or maybe it’s just because maps are pretty but there’s nothing more fun than tinkering with location data.

However, reading in spatial data, especially large data sets can sometimes be a pain. Here are some simple things to consider when working in spatial data in R and breaking large data sets into more manageable chunks.

Click through for three tips when dealing with spatial data. The code is in R but the tips make sense in any language.

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ggbrick in CRAN

Published 2024-03-22 by Kevin Feasel

Dan Oehm notes another brick in the wall:

If you’re looking for something a little different, ggbrick creates a ‘waffle’ style chart with the aesthetic of a brick wall. The usage is similar to geom_col where you supply counts as the height of the bar and a fill for a stacked bar. Each whole brick represents 1 unit. Two half bricks equal one whole brick.

It has been available on Git for a while, but recently I’ve made some changes and it now has CRAN’s tick of approval.

Click through to see how you can use it. This style of waffle chart, in the right scenario, can be quite useful, providing a high-level view and also giving you some idea of fine-grained magnitudes. H/T R-Bloggers.

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Ways to Use Sort Order in Bar Charts

Published 2024-03-21 by Kevin Feasel

Mike Cisneros demands order:

When you’re visualizing categorical data, sorting the bars in your chart is usually a straightforward task. Or is it?

In most cases, you probably take the category with the largest value and stick that in the prime spot, the leftmost slot on the horizontal axis. Then, you proceed from left to right in descending order of value. Easy peasy.

But it’s not always that simple, as Mike points out.

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Plotting Training and Testing Results with tidyAML

Published 2024-03-18 by Kevin Feasel

Steven Sanderson builds a plot:

In the realm of machine learning, visualizing model predictions is essential for understanding the performance and behavior of our algorithms. When it comes to regression tasks, plotting predictions alongside actual values provides valuable insights into how well our model is capturing the underlying patterns in the data. With the plot_regression_predictions() function in tidyAML, this process becomes seamless and informative.

Read on to see how the function works and the kind of result you can expect from it.

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Improving Data Labels with Format Strings

Published 2024-03-06 by Kevin Feasel

Kurt Buhler has some new digs:

Format strings greatly improve the usefulness of your model, particularly when you apply custom and dynamic format strings creatively. However, there are considerations to keep in mind.

It is important that the values in a report display for users as they expect. Effective formatting of DAX measures and table columns improves your model, as values are easier to read and interpret. While formatting may seem simple at first glance, the flexibility of DAX and format strings in Power BI can create many opportunities for more creative and efficient tables or visuals.

Click through to understand why proper formatting of measures is so important on dashboards, and also congratulate Kurt on becoming an Italian. At least, I assume citizenship conveys when you do work for Marco & Alberto.

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Accessibility in UI Design

Published 2024-02-26 by Kevin Feasel

Benedict Ampea-Badu shares some tips:

In this last segment of the series, we’ll delve into the crucial elements of navigation and flow, exploring further the part of web accessibility that ensures users can effortlessly navigate online content. Additionally, we’ll shine a spotlight on the indispensable practice of regular testing, an ongoing commitment that goes beyond compliance, providing invaluable insights into real user experiences and fostering continuous improvement.

Ensuring a seamless online experience for everyone and facilitating smooth navigation boils down to adhering to the fundamentals of web accessibility. It boils down to carefully planning how websites are laid out, making it easy for users to explore different things effortlessly. When developers grasp how users interact and tackle possible issues, they go beyond just ticking boxes on a checklist. Instead, they create websites that truly put users first, considering how people actually use and prefer to browse.

This is particularly about accessibility in web applications but many of the same principles apply to things like Power BI reports.

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Adding Superscripts and Subscripts to Axis Labels in R

Published 2024-02-22 by Kevin Feasel

Steven Sanderson changes the script:

Before we dive into the code, let’s quickly review what superscripts and subscripts are.

  • Superscripts: These are smaller-sized characters or numbers that appear above the baseline of the text. They are often used to denote exponents or indices.
  • Subscripts: On the other hand, subscripts are smaller-sized characters or numbers that appear below the baseline of the text. They are commonly used in mathematical expressions or chemical formulas.

Read on to see how you can generate these in R visuals.

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