In this module you will learn how to use the Waffle Chart Power BI Custom Visual. The Waffle Chart visual is most useful for presenting a percentage of data. This chart is a great option to choose over other visuals like Pie Charts, which are not great at showing proportions of data.
Waffle charts are infographic-friendly visuals; they’re easy to read and as long as you don’t have too many categories, easy to compare.
This visual is a mixture between a 100% stacked column chart and a 100% stacked bar chart.
The width of a column is proportional to the total value of the column.
With a relatively small number of groups for both columns and rows, this is a good way of getting a feel for relative weights across two dimensions.
If you select a text column you can:
- Show only the first attribute
- show only the last attribute
- Count the attribute
- Distinct count the attribute
If you select a numeric column you can:
Sum of value
find the minimum or maximum value
Average the value of column
standard deviation of value
Count the value
Distinct count of value
Variance fo value
Median of value
The screenshots are in Italian, but it’s pretty easy to get the context behind them.
Yesterday I published the blog post Dynamically Changing Shapes in Power BI, which seemed to be quite popular in social media. It showed a lot of people were struggling with this issue and that some people had also found (alternative) solutions for it. In the comments of that blog post, you can find a solution proposed by Jason Thomas (blog | twitter). Jason has quite the Power BI & SSRS knowledge and he has found a cool trick to solve our changing images problem. In this blog post, I’m going to explain the solution step-by-step.
Click through to see the solution.
My wife loves to travel AND she loves data, so it’s no surprise that she showed me the infographic in question.
“Oh come on, California residents don’t visit the Philippines more often than any other country.” That was my first reaction. (Mexico is the overwhelming #1 destination, basically for every state… because Cancun. And because there are so many Mexican-Americans).
“Ah… but California residents DO visit the Philippines disproportionately more often than they ‘should,’ according to national averages!” That was my dawning second realization (and confirmed by the fine print of the Orbitz article, even though the article’s title suggests otherwise.)
So, how do we do that in DAX? Pretty simply, actually.
I’m mentally working out whether this could be useful in anomaly detection.
The Dual KPI efficiently visualizes two measures over time. It shows their trend based on a joint timeline, while absolute values may use different scales, for example Profit and Market share or Sales and Profit.
Each KPI can be visualized as line chart or area chart. The visual has dynamic behavior and can show historical value and the change from the latest value when you hover over it. It also has small icons and labels to convey KPI definitions and alerts about data freshness.
I looks cool, but I dunno; my philosophy is that man cannot serve two KPIs.
In this module you will learn how to use the Gap Analysis Power BI Custom Visual. The Gap Analysis visual is used to analyze the difference between two different groups of data you have. For example, you might use it to analyze the gap between two answers people gave in survey response data.
I like the gap analysis visual; it works well as a cross-category comparison visual, giving you an idea of the relative importance of each category as well as the change from one time period to the next. It’s a good way of fitting two useful pieces of information into the same visual.
You can insert images into Power BI Desktop, but these are static images. If you want them to dynamically change, you need the Image Viewer custom visual. Unfortunately, it doesn’t support measures, only columns. Since we want dynamic changes, fixed column values are not going to work. Someone proposed a work around on the Power BI forums, but this only works if you have a fixed set of attributes you want to slice on (for example, 4 categories). I want a totally flexible solution (e.g. each month we have a couple of new weeks to slice on), so again, not possible.
The only solution I could think of that would still work: using R visuals.
Read on for the solution.
Cedric Charlier continues his series on fixing up an Excel file. First up is turning results into an enumeration:
We’ve previously decided that a DON’T KNOW, shouldn’t influence our average of the answers. To apply this decision, we just need to filter the table
Resultand remove all the values equal to
0(Enum value of DON’T KNOW). Then we calculate the average and subtract 1 to get a value between 0 and 4. Coooool, except that if we’ve no value non equal to 0, it will return -1 … not what we’re expecting. We’ll need to validate that the average is not null before subtracting
The next post involves converting respondent information into a dimension:
In this table, only the results with a
111really interest me for a merge with the existing table
Respondent. If you’re familiar with the UI of Power BI Desktop then you’ll probably think to create a new table referencing this one then filter on
111and finally merge. It’ll work but applying this strategy could result in many “temporary” tables. A lot of these small tables used only for a few steps before merging with other tables tend to be a nightmare for maintenance. You can use the “Advanced formula editor” to not display this kind of temporary tables and embed them in your main table.
Read on for more.
A normal slicer can be tedious when you want to show everything apart from just one or two entries in your filtered tiles – don’t take your finger off the Ctrl key! You could always turn on Select All, then unselect the items. But you may not want Select All enabled, and it’s not available for chiclets. Or you could use Visual/Page/Report level filters, but these are not available in dashboards or publish-to-web. So you may be interested in an anti-slicer? There are many ways to do this, this is one approach.
This is an interesting problem to solve, and I think this is a nice solution.