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Category: Visualization

Making a Better Pie Chart

Published 2020-02-28 by Kevin Feasel

Elizabeth Ricks tries the impossible:

A friend called me recently and started our conversation with: “I know you dislike pie charts, but…can you help me create one?” 

Spoiler alert: I don’t hate pie charts. They’ve received a bad rap over the years and with good reason—they are very commonly used when another chart type would be better suited. The appropriate use case for a pie chart is expressing a part-to-whole relationship. Their limitation is that it can be difficult to accurately judge the relative size of and compare the segments. Here are some related articles on our blog: the great pie debate and an updated post on pies. 

Elizabeth does put together the best possible case, but I’m still in favor of burning pie charts to the ground.

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Creating a Power BI Report Book

Published 2020-02-21 by Kevin Feasel

Teo Lachev shows us how to build a Power BI report book:

Scenario: Management has requested an easy way to view a subset of strategic reports located in different Power BI workspaces. You can ask the users to mark reports and dashboards as favorites so they can access pertinent content in the Favorites menu, but you’re looking for an easier configuration, such as to create a book of reports with a built-in navigation that organizes reports in groups (like a table of contents), such as the screenshot below demonstrates.

Click through for the instructions as well as a discussion on why you wouldn’t necessarily want to build a Power BI app for this.

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Digging Into Bar Charts

Published 2020-02-20 by Kevin Feasel

Alex Velez takes us through the humble bar chart:

Our eyes start at the base and scan towards the end of each bar. We measure the lengths relative to both the baseline and the other bars, so it’s a straightforward process to identify the smallest or the largest bar. We can also see the negative space between varying heights of bars to compare the incremental difference between them. 

Not only are these graphs easy to read, but they are also widely recognized. Chances are, you’ve already encountered a standard horizontal or vertical bar chart. But bars come in many shapes and sizes. I’ll list below a few of the most common variations, with links to examples.

Click through for some good information on bar charts, including design tips.

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Publishable Adverse Event Tables in R

Published 2020-02-13 by Kevin Feasel

Inge Christoffer Olsen shows how to clean up tables in R for publication:

The summary of Adverse Events is a nice table just summing up the adverse events in the trial. Note the “[N] n (%)”-format which is the number of events, number of patients with events and percentage of patients with event.

This particular example is about adverse events, but the key concepts in the code apply to many kinds of tables you want to make look a bit nicer. H/T R-Bloggers

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Audio Analysis in R

Published 2020-02-04 by Kevin Feasel

Jeroen Ooms walks us through some audio analysis with R and the av package:

The latest version of the rOpenSci av package includes some useful new tools for working with audio data. We have added functions for reading, cutting, converting, transforming, and plotting audio data in any popular audio / video format (mp3, mkv, aac, etc).

The functionality can either be used by itself, or to prepare audio data for further analysis in R using other packages. We hope this clears an important hurdle to use R for research on speech, music, and whale mating calls.

One of the most interesting things I saw Edward Tufte demonstrate was visualizing music using the Music Animation Machine. There’s a lot of space here to experiment. H/T R-Bloggers.

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Fun with Palindromic Dates

Published 2020-02-03 by Kevin Feasel

Tomaz Kastrun has a bit of fun with the date February 2, 2020:

As of writing this blog-post, today is February 2nd, 2020. Or as I would say it, 2nd of February, 2020. There is nothing magical about it, it is just a sequence of numbers. On a boring Sunday evening, what could be more thrilling to look into this little bit further 🙂

Let’s kick R Studio and start writing a lot of useless stuff.

Tomaz also compares US versus EU palindromic dates and visualizes the different distributions.

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Dealing with Big Ranges in a Graph

Published 2020-01-24 by Kevin Feasel

Alex Velez shows how we can work with a particular case of problem:

Today’s post is about a common challenge: when one data series is so large relative to the others that a single scale makes it nearly impossible to see any details. Consider the following line graph. It displays state and local revenue by transportation mode, which I created using data from the Bureau of Transportation Statistics 2018 Report.

Alex has one solution. Another idea could be to change the Y axis to log scale, especially because you’re dealing with money. That would tighten up the series and allow for more information to be displayed on the single graph.

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Building a Dual-Axis Line Chart in Power BI

Published 2020-01-24 by Kevin Feasel

Matt Allington shows how you can build a dual-axis line chart in Power BI:

Unfortunately, Power BI does not support a dual axis line chart as a standard visual at this time. The good news however is there is a custom visual called “Multiple Axes chart by xViz” that can do this in Power BI.  This visual has been around for a while, but there have been some formatting issues (in my view) that prevented it being a solution to this problem – that is now fixed).  I will demonstrate how to set up a dual axis charge using the Adventure Works database and this visual.

Honestly, I’m pretty happy that Power BI does not support a dual-axis line chart. It is the cause of so many instances of spurious correlation that I’d err on the side of not including multiple axes.

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Displaying SSRS Usage Stats Through Grafana

Published 2020-01-15 by Kevin Feasel

Alessandro Alpi takes queries to view SQL Server Reporting Services data and visualize it in Grafana:

One of the problems that often occur in our organization as well as some of our customers, is to get immediate feedback about usage statistics of reports. Usually, the request of creating reports is out of control and some of them are executed only “that time” and not anymore. In the worst-case scenario, many of them aren’t executed at all and some of them could become even overlapped or duplicated.

Therefore, it is important to know the usage statistics, user by user and report by report, to make the reader aware of them, let him interpreting the values of the same query in multiple ways and graphical layouts. While this is not possible with a tabular format (unless you export the values using any external tools such as Excel) it is simpler when it comes to a dashboard.

And that’s where Grafana excels.

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