A Fine Slice Of SQL Server
Zenguo Zhang teaches a lesson:
In
ggplot2, when displaying grouped data along categorical axes (such as grouped bar charts, boxplots, or error bars), horizontal dodging is used to prevent elements from overlapping at each categorical position.ggplot2provides two primary dodging position functions:position_dodge()andposition_dodge2().
Click through or else Piccolo is going to yell again.
Leave a CommentCole Nussbaumer Knaflic guides the non-thinking machine:
Now that we have the story planned, it’s time to start developing the content that will support our message and narrative. When data is part of that, a good first step is choosing a visual that aids in comprehension. The right graph makes your point immediately clear. The wrong one makes your audience spend their mental energy decoding the graph instead of understanding your message.
This is where people sometimes stumble. They use the first chart that comes to mind—or simply carry forward the one they used during exploratory analysis. But a graph that works for exploring data isn’t necessarily the best for communicating it. Your audience and takeaway should drive the choice. By this point, you’ve already done that work: you know your audience, you’ve planned your story, and you’ve written takeaway titles that tell you exactly what each graph needs to show. Let those sentences guide your design.
As you’d expect, there’s some good advice on choosing specific types of visuals. But the majority of this article is around nudging the language model to spit out the correct visual for the right reasons.
Leave a CommentDBAs spend time dealing with SQL Server performance, capacity, monitoring, troubleshooting, provisioning, etcetera; I’ve previously mentioned that R is a powerful, open-source language with a great ecosystem of libraries for analysis and visualisation, so it’s no surprise that I think mixing SQL Server and R Markdown for reporting goes together like a Vegemite and cheese sandwich…lunch perfection!
Here’s a couple of real-world examples of how I’ve used R Markdown connected to SQL Server (for a recap of how to do this from a technical perspective, see my earlier blog post “Connecting to a SQL Server database from R Markdown”):
This is a neat approach to visualizing database backup times as a process control chart.
Leave a CommentAmy Esselman provides some guidance:
One of our top tips for explanatory communications is to use color sparingly and purposefully to help your audience understand your data and message. Color should be an explicit choice, not something your software applies by default, whether that’s a graphing tool or an AI assistant generating your first draft. These tools can build a chart in seconds. They might even add highlighting on their own. But they don’t know which data matters most to your audience. That call is still yours. Used thoughtfully, color is often one of the quickest ways to improve a graph.
Color is an extremely powerful pre-attentive attribute, meaning that it’s something we intuitively see and respond to without explicit thought. That’s why choosing what to color can be so powerful. If everything has bright, distracting colors, you lose an avenue to guide the viewer’s eye. But Amy’s example is a good one to show the particular element(s) in the visual that you want people to focus on, and the viewer’s eyes will automatically go there.
Leave a CommentAndrea Onofri builds a complex chart:
I have often found myself needing to plot a single graph with two y-axes having different scales. For example, this might be useful for representing temperature and rainfall data at a given location. Unfortunately, doing this with
ggplot()is not straightforward.
As Andrea mentions, there are specific circumstances in which having a dual-axis chart is reasonable, and click through to learn how. ggplot2 tends to be rather opinionated regarding visual choice and design. I happen to like those opinions and think they are generally correct, but I can also recognize that there may be exceptions to the rules. For those instances, I think “Somewhat difficult but not impossible” is a solid answer, as it keeps people from doing things inappropriately with a couple of mouse clicks, like setting up those stupid 3D bar charts in Excel. H/T R-Bloggers.
Leave a CommentMicrosoft recently introduced a new default visual design style for Power BI named Fluent 2. I personally disagree with a few choices in the new defaults, including the removal of alternating row colors from Table and Matrix visuals.
Click through to see how you can bring back alternate row shading.
Comments closedMauricio Vargas Sepulveda has released an R package:
The goal of spuriouscorrelations is to keep alive the amazing examples from Tyler Vigen. Unfortunately, as of 2023-10-09, the website is down as my students noticed. Therefore, I decided to use the snapshot from the Internet Wayback Machine to save the datasets from 2023-06-07.
Click through to see how you can re-live those old charts, using the example of “number of people who drowned by falling into a pool” versus “films Nicolas Cage appeared in” on an annual basis. H/T R-Bloggers.
Comments closedThomas Williams is back with more:
In my last post on improving inputs in R Markdown/Shiny, I covered four improvements to quality of life in interactive reports and dashboards. In this blog post I have three more, all approaches I’ve used to add professionalism to self-service R Markdown files.
In yet another plug for R Markdown: most of these techniques can be used in a single *.Rmd file, or can be included in many by putting them in a common CSS or javascript file and linking to it.
Click through to see what you can do.
Comments closedMarco Russo and Alberto Ferrari format things differently:
A challenging requirement in Power BI reports is that of applying different formatting rules based on the level of aggregation. At the year level, the background shade may reflect each year’s share of the grand total. At the quarter level, a status color may indicate whether the quarter is above or below the average. At the month level, the color may flag exceptional values, like months that contribute more than a defined threshold to their year. Each level has its own logic; what the conditional expression of the measure needs to know is which level the current cell belongs to.
Read on to see how you can pull this off.
Comments closedTeo Lachev takes a look at a new preview:
The June release of Power BI Desktop includes a preview of a new Power BI slicer configuration – Date Picker. It’s meant to solve two issues with report design.
Read on to see what those two issues are and how this new date picker can resolve them. It’s still in preview, so you’d have to change the settings in Power BI Desktop. And I imagine it won’t be available in Power BI Report Server because those people (including me) can’t be trusted to have nice things.
Comments closed