A Fine Slice Of SQL Server
Matt Allington shows how you can apply conditional formatting to non-numeric fields in Power BI:
The high level process is to:
1. Create a measure that returns a colour as the result1. It can be a word, such as blue, red, green
2. It can be a hex code for a colour, like #40E0D0″, “#FFA07A”
2. Use conditional formatting and use the measure to apply the formatting on the text as a rule.
Read on for a demo.
Comments closedDavid Eldersveld shows how to create running totals in both Tableau and Power BI:
What about a separate Power BI Date table?
This setup is built for consistency of comparison. As people go deeper into Power BI, they typically add a separate Date table as part of a more robust data model and add relationships between tables. At the same time, they disable the default Auto Date/Time built-in hierarchies. This more advanced setup with a separate Date table allows several conveniences as well as performance and storage benefits. It’s especially true with larger models that include many facttables that each join to Date and other possible dimension tables. Tableau doesn’t currently have a comparable data model. We’ll stay conveniently away from that setup in Power BI because we only have one simple sample table.
I think both of them make this an easy operation, though Tableau is probably easier here.
Comments closedLaura Ellis takes us through ggplotly:
As someone very interested in storytelling, ggplot2 is easily my data visualization tool of choice. It is like the Swiss army knife for data visualization. One of my favorite features is the ability to pack a graph chock-full of dimensions. This ability is incredibly handy during the data exploration phases. However, sometimes I find myself wanting to look at trends without all the noise. Specifically, I often want to look at very dense scatterplots for outliers. Ggplot2 is great at this, but when we’ve isolated the points we want to understand, we can’t easily examine all possible dimensions right in the static charts.
Enter plotly. The plotly package and ggploty function do an excellent job at taking our high quality ggplot2 graphs and making them interactive.
Read on for several quality, interactive visuals.
Comments closedDaniel Oehm shares two techniques for using custom fonts in your ggplot2 visuals:
ggplot – You can spot one from a mile away, which is great! And when you do it’s a silent fist bump. But sometimes you want more than the standard theme.Fonts can breathe new life into your plots, helping to match the theme of your presentation, poster or report. This is always a second thought for me and
need to work out how to do it again, hence the post.
There are two main packages for managing fonts– extrafont, and showtext.
Read on to see how to use each of these packages. H/T R-bloggers
Comments closedReza Rad shows us how to add a totals figure to Power BI stacked column charts:
As you can see, there are data labels for each subcategory (means gender and education), but no data label showing the total of each education category. for example, we want to know how much was the total sales in the High School category. Now that you know the problem, let’s see a way to fix it.
Read on for Reza’s solution to the problem. In general, if people might care about the total, do them a favor and show the total.
Comments closedThomas Lin Pedersen announces a new version of ggforce for R:
If there is one thing of general utility lacking in ggplot2 it is probably the ability to annotate data cleanly. Sure, there’s
geom_text()/geom_label()but using them requires a fair bit of fiddling to get the best placement and further, they are mainly relevant for labeling and not longer text.ggrepelhas improved immensely on the fiddling part, but the lack of support for longer text annotation as well as annotating whole areas is still an issue.In order to at least partly address this, ggforce includes a family of geoms under the
geom_mark_*()moniker. They all behaves equivalently except for how they encircle the given area(s).
There are some really interesting features in the ggforce package, so check them out.
Stephanie Evergreen shows how you can improve your visuals by removing most of the lines:
The Lines section of the Data Visualization Checklist helps us enhance reader interpretability by handling a lot of the junk, or what Edward Tufte called the “noise” in the graph. I’m referring to all of the parts of the graph that don’t actually display data or assist reader cognition. Create more readability by deleting unnecessary lines.
The default chart, on the left, has black gridlines. These stand out quite a bit because of how well black contrasts against the white chart background. But the gridlines shouldn’t be standing out so much because they are not the most important part of the graph
I like that Stephanie keeps the gridlines. I’ve seen Tufte advocate removing them altogether but there’s a lot of value in keeping them in; just don’t make them the sharpest focus color.
Comments closedMartin Monkman has an update to the MLB run scoring app in Shiny, just in time for spring training:
2. feather instead of csv
The app relied on some pre-wrangled csv files; these have been replaced by files stored using the .feather format, which makes for a signficant performance improvement.
Martin has made a significant number of changes and it’s cool to see the full list of changes. H/T R-bloggers
Comments closedShannon Holck has shared a Power BI theme using a color-safe and easy to view palette:
Edward Tufte recommended use of soft colors that do not tire the eyes. I’ve actually never read his books (yet), but a former boss of mine was a devout disciple and produced some beautifully soft color palettes.
Stephen Few, in “Show Me the Numbers,” reiterated Tufte’s color theories and recommended three sets of hues:
Light – for large shapes, e.g. bars
Medium – for small shapes, e.g. points
Dark/Bright – for calling attention to data
Click through for more including where you can get this Power BI theme. I’m not exactly the world’s biggest fan of the default palette so I’ll have to check this one out.
Comments closedReza Rad shows us a few ways to perform conditional formatting in Power BI:
I have given many presentations and talks about Data Visualization, and still, I am amazed by how many visualizations I see which is not following the basic rules. In this article, I want to focus on table visual. A table is a visual that most of us are using it on many occasions, in fact, many users, like to see the data in table format. However, a table can be visualized in a way that is not readable. In this article, I’m showing you the most common style of a table which many report developers use, and then challenge it with a better style. The mystery is of course in conditional formatting. Like all my other articles, this article is demonstrating this technique in Power BI. If you like to learn more about Power BI, read Power BI book from Rookie to Rock Star.
Some of these formats are better than others, but you do have the power to do quite a bit with it in Power BI.
Comments closed