A Fine Slice Of SQL Server
John Lafleur has a method to ensure depression:
In this article, we will show you how you can understand how much your team leverages Zoom, or spends time in meetings, in a couple of minutes. We will be using Airbyte (an open-source data integration platform) and Tableau (a business intelligence and analytics software) for this tutorial.
Click through for the tutorial.
Comments closedNick Campion takes us through working with Graphite:
Graphite is a free and open-source software. It is used as a time-series database monitoring tool, where you can collect, store and display time-series data in real-time. As you can monitor certain metrics of this data using Graphite, it has a very useful and simple dashboard used to visualize these metrics.
This article will show you how to display a metric on your Graphite dashboard.
Click through for more information.
Comments closedNeil Saunders takes a look at a classic chart:
I first heard Florence Nightingale and her Geeks Declare War on Death, an episode of the Cautionary Tales podcast, premiered as a special episode of 99% Invisible. It discusses Nightingale’s work as a statistician and in particular, her visualisation of mortality causes in the Crimean War using the famous “rose chart”, or polar area diagram.
I’m sure you’re thinking: how can I explore that using R?
Read on to find out.
Comments closedThe folks at Jumping Rivers conclude a series:
As with many aspects of programming, when you are working by yourself you can be (slightly) more lax with styles and set-up. However, as you start working in a team, different styles can quickly become a hindrance and lead to errors.
Using {knitr} is no different. When you work on documents with different team members, it’s helpful to have a consistent set of settings. If the default for
evalchanges, this can easily waste time as you try to track down an error. At Jumping Rivers, we use {knitr} a lot. From our training courses, to providing feedback to clients, to constructing monthly reports on clients infrastructure. The great thing about {knitr} is it’s really easy to customise. The bad thing is that without some care, it’s really easy for every member of the team to have different default options. This proliferation of different default options, means that when we pick up someone else document, mistakes may creep in.
Read on for different options they use to keep things consistent.
Comments closedThe folks at Jumping Rivers continue a series on knitr and rmarkdown:
In this third post, we’ll look at including eternal images, such as figures and logos in HTML documents. This is relevant for all R markdown files, including fancy things like {bookdown}, {distill} and {pkgdown}. The main difference with the images discussed in this post, is that the image isn’t generated by R. Instead, we’re thinking of something like a photograph. When including an image in your web-page, the two key points are
– What size is your image?
– What’s the size of your HTML/CSS container on your web-page?
Read the whole thing.
Comments closedDave Ruijter has an interesting browser plugin:
If you’re working with multiple Azure Databricks workspaces at the same time it can be very hard to keep those workspaces apart. Personally I struggled to keep track of the dev / tst / acc / prd workspaces. Luckily, Henko had the answer: color them differently!
Click through to learn more about the browser extension and how to use it with Databricks.
Comments closedThe folks at Jumping Rivers continue a series on image optimization:
As the JPEG compression algorithm significantly reduces file size, JPEG files are ubiquitous across the web. If you take a photo on your camera, it’s almost certainly using a JPEG storage format. Historically the file extension was
.jpgas Microsoft Windows only handled three character file extensions (also.htmvs.html). But today both extensions are used (personally I prefer.jpeg, but I’m not very consistent if I’m totally honest).If you did a little Googling on which file format to use for images, then the answer you would come across is that JPEG’s are the default choice. But remember, figures are different from standard images!
Click through for a review of three viable image formats.
Comments closedElizabeth Ricks shows how to include data labels on a line chart in Excel:
Today’s post is a tactical one for folks creating visuals in Excel: how to embed labels for your data series in your graphs, instead of relying on default Excel legends.
To illustrate, let’s look at an example from storytelling with data: Let’s Practice!. The graph below shows demand and capacity (in project hours) over time.
It is significantly more complicated than you might first think.
Comments closedLouis Davidson shows how you can visualize data stored in SQL Server graph tables:
Each node object has its own surrogate key values that start at 0, so if you are going to use the code for more than one node at a time, you have to make the surrogate values unique for the TGF file (see the last blog on importing for more details on that). In the code I make a temp table to stage the objects, so if you have > 1 node, the second set of keys need to start off where the previous ones left off. So the code uses an identity column, and joins to that identity column by schema, table, and edgeId, outputting the unique key:
Read on to see how Louis translates the data into the right format for visualization.
Comments closedThe Jumping Rivers team shares some insight on image creation:
In this series of posts we’ll consider the (simple?) task of generating and including figures for the web using R & {knitr}. Originally this was going to be a single post, but as the length increase, we’ve decided to separate it into a separate articles. The four posts we intend to cover are
– setting the image size (this post)
– selecting the image type, PNG vs JPEG vs SVG
– including non-generated files in a document
– setting global {knitr} options.
Read on for the first post in the series.
Comments closed