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Category: Visualization

The Value of KPIs and Cards in Power BI

Published 2023-09-05 by Kevin Feasel

Kurt Buhler and Stepan Resl give you a card:

When a user arrives at your report, they should be able to answer their most important questions in a few seconds. To do this, we typically put the most critical information in the top-left of the report (where we often look first). This information should provide a high-level overview, whereas additional details should be placed at the bottom of the report, behind interactions, or on later pages.

An effective and popular way to call attention to important numbers in Power BI is by using cards and KPI core visuals.

Read on for several examples and a breakdown of how they work best.

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Building Correlation Heatmaps in R

Published 2023-08-31 by Kevin Feasel

Steven Sanderson shows two packages for building heatmaps in R:

Data visualization is a powerful tool for understanding the relationships between variables in a dataset. One of the most common and insightful ways to visualize correlations is through heatmaps. In this blog post, we’ll dive into the world of correlation heatmaps using R, using the mtcars and iris datasets as examples. By the end of this post, you’ll be equipped to create informative correlation heatmaps on your own.

Read on to see how to build heatmaps with the corrplot and ggcorrplot packages.

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Visualizing when Lower is Better

Published 2023-08-30 by Kevin Feasel

Alex Velez inverts a common experience:

When quickly scanning, I wonder why the direct and indirect sales teams underperformed in 2022. Mostly, they fell below the goal of 90 days, exceeding their target only three times. 

Now, pausing to think more critically about the context of this scenario, I realize I’ve misread the graph—specifically the goal line. Targets and goals are often seen as minimum thresholds, not maximum limits. But in the sales industry, the goal is to close a deal as quickly as possible. In this visual, below the goal line is actually a good thing!

This graph challenges my standard construct of targets and goals, which could lead to confusion or, worse, the wrong conclusions if I’m not careful. 

Read on for five alternative ways to display this graph and (hopefully) reduce confusion.

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Setting Table and Matrix Column Widths in Power BI

Published 2023-08-30 by Kevin Feasel

Kurt Buhler controls the horizontal, Kurt Buhler controls the vertical:

One challenge of the table and matrix visuals in Power BI is that it’s difficult to precisely and consistently set column widths. Unlike in Excel, where you can set the row and column widths in a spreadsheet, you have no option in the visual interface to control the column width property. However, it’s still possible to control it in the report metadata, which is exposed in the officially supported Power BI Projects format (.pbip) which is in preview. Notably, however, opening and modifying report metadata from this format isn’t yet supported. Despite that fact, it still works reliably, so I thought I’d demonstrate how to do this.

There are a fair number of steps involved but it all makes sense in the end.

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Plotting Multiple Histograms in R

Published 2023-08-28 by Kevin Feasel

Steven Sanderson shows us two libraries to plot two histograms:

Histograms are a powerful tool for visualizing the distribution of numerical data. They allow us to quickly understand the frequency distribution of values within a dataset. In this tutorial, we’ll explore how to create multiple histograms using two popular R packages: base R and ggplot2. By the end of this guide, you’ll be able to confidently display multiple histograms on a single graph using both methods.

Click through for more than two examples.

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Visualizing Univariate Data Distributions in R

Published 2023-08-25 by Kevin Feasel

Steven Sanderson reviews the shape of the data:

Understanding the distribution of your data is a fundamental step in any data analysis process. It gives you insights into the spread, central tendency, and overall shape of your data. In this blog post, we’ll explore two popular functions in R for visualizing data distribution: density() and hist(). We’ll use the classic Iris dataset for our examples. Additionally, we will introduce the {TidyDensity} library and show how it can be used to create distribution plots.

Click through for three different functions for visualizing the density of a variable.

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Adding Mean to Box Plots in R

Published 2023-08-24 by Kevin Feasel

Steven Sanderson tracks the sixth number of a five-number summary:

Data visualization is a powerful tool for understanding and interpreting data. In this blog post, we will explore how to create box plots with mean values using both base R and ggplot2. We will use the famous iris dataset as an example. So, grab your coding tools and let’s dive into the world of box plots!

Note that this is mean in addition to median in these visuals, not replacing the median.

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Creating a Box Plot in R

Published 2023-08-21 by Kevin Feasel

Steven Sanderson builds up a box plot:

Are you ready to dive into the world of data visualization in R? One powerful tool at your disposal is the box plot, also known as a box-and-whisker plot. This versatile chart can help you understand the distribution of your data and identify potential outliers. In this blog post, we’ll walk you through the process of creating box plots using R’s ggplot2 package, using the airquality dataset as an example. Whether you’re a beginner or an experienced R programmer, you’ll find something valuable here.

Click through to learn what kind of information a box plot can provide, as well as how to create one using a variety of R libraries.

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Fallback Fonts in Power BI and Deneb Visuals

Published 2023-08-18 by Kevin Feasel

Meagan Longoria gets a request:

This week, I was working with a client who requested I use the Segoe UI font in their Power BI report. The report contained a mix of core visuals and Deneb visuals. I changed the fonts on the visuals to Segoe UI and published the report. But my client reported back that they were seeing serif fonts in some visuals. I couldn’t replicate this on my machine while viewing the report in a web browser or in Power BI Desktop.

Read on to see what the problem was, as well as the workaround.

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Creating Curves in R

Published 2023-08-17 by Kevin Feasel

Steven Sanderson draws a curve:

In the vast world of R programming, there are numerous functions that provide powerful capabilities for data visualization and analysis. One such function that often goes under appreciated is the curve() function. This neat little function allows us to plot mathematical functions and explore their behavior. In this blog post, we will dive into the syntax of the curve() function, provide a couple of examples to demonstrate its usage, and encourage readers to try it on their own.

Click through for several examples.

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