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Category: Visualization

Designing for Red-Green Color-Blindness

Published 2019-08-12 by Kevin Feasel

Andy Kirk has a few tips to help you design for people who have deuteronopia or protanopia:

Many visualisations use colours to represent data values, either to show quantitative scales or categorical classifications. One of the most common colour metaphors used in visual displays involves the use of a red-green colour scheme, sometimes known as “RAG” or “traffic light” colours. These colours are used to convey notions of green = ‘good’ or ‘above average’ and red = ‘bad’ or ‘below average’ in some cultures, and the reverse in others. Such colour connotations are long-established and widely used, especially in financial or corporate contexts, but whilst they provide a certain immediacy in their meaning for many viewers, around 4.5% of the population are colour-blind (8% of men) with the red-green colour deficiency “Deuteranopia” being the most common form. This means a significant proportion of viewers may not be able to perceive important such visual encodings.

I’m not the biggest fan of some of them, but there are some really good ideas in here.

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Guiding Your Users with Power BI

Published 2019-08-09 by Kevin Feasel

Marc Lelijveld continues a series on storytelling with Power BI:

Another thing to think about before building visuals, is the click path. In order to make sure we’re really telling the story, we need to get our click path in a logical order. This is most important for both, declarative and exploratory storytelling.

Maybe you want to provide all the information in your visuals right away. Sometimes I see things like this happening when people add a lot of visuals on only one page. In my experience it is better to make your report interactive and work with multiple pages. Spread the story you want to tell out over multiple pages. This is what Will Thompson also has done as well in this report for the Gartner Bakeoff in 2018.

This sort of planning helps you out in the long run.

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Drawing SSIS Packages

Published 2019-08-07 by Kevin Feasel

Bartosz Ratajczyk continues a quest to draw SSIS packages as SVGs:

To get the Value and Expression properties I need to find the precedence constraint in the .dtsx file during the XSL transformations. It requires three changes in the package2svg.xsl:

– I have to pass the name of the .dtsx file
– I have to read the XML from the .dtsx file
– I have to use the DTS namespace because it’s the namespace of the .dtsx file

Read on for more. Bartosz to this point has covered the control flow.

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Using Bookmarks for Power BI Filters

Published 2019-08-02 by Kevin Feasel

Marc Lelijveld continues a series on storytelling with Power BI:

As said, being dynamic is a broad concept. Lets use the above shown example. As a report author, we can define that the end-user should be looking at an top 10 ranking of countries (right side of the report). Since the difference between number 9 and 10 in the ranking is so small, you might want to know what the difference is to number 11. Now, we can’t see that. We need to change the filter context to see the rest of the ranking.

Click through for a step by step example of what to do.

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Updated Power BI Violin Chart

Published 2019-08-01 by Kevin Feasel

Meagan Longoria reviews an update to Daniel Marsh-Patrick’s violin chart custom visual in Power BI:

First, the violin plot is now a certified custom visual. This means that it has been tested by the Power BI team to ensure it meets certain requirements, one of which is that the visual does not access external services or resources. You can be confident your data isn’t being sent externally when you use the violin plot.

As for the functional enhancements, a new legend has been added. This is a great addition to make the chart clearer and more easily read, especially for audiences that may not be familiar with how the violin plot works. The customizable legend calls out what markers are used for mean, median, and quartiles.

Meagan is quite pleased with these updates.

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An Intro to k-Means Clustering

Published 2019-07-30 by Kevin Feasel

Holger von Jouanne-Diedrich takes us through an example of how k-means clustering works:

The guiding principles are:

– The distance between data points within clusters should be as small as possible.
– The distance of the centroids (= centres of the clusters) should be as big as possible.

Because there are too many possible combinations of all possible clusters comprising all possible data points k-means follows an iterative approach

Click through for a demonstration. I appreciate adding visualizations for intermediate steps in there as well because it gives you an intuitive understanding for what the one-liner function is really doing.

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Easy Navigation with Power BI

Published 2019-07-30 by Kevin Feasel

Marc Lelijveld has started a series on storytelling with Power BI. Part one is all about navigation:

Providing an easy navigation is important for the usability of your report. In order to make it as intuitive as possible, you should think as an end-user. By opening a report, where do you expect the navigation to be?

If you open the first webpage you can think of, most likely you will find the navigation on top or on the left side. Which is totally reasonable (at least according to my opinion) since we read from left to right and from top to bottom.

By default in Power BI you will have the navigation on the bottom where you can switch between your report pages. But we just concluded that it is more intuitive to put your navigation on top or on the left side. So why not do the same with your Power BI reports? We can do this by creating our own navigation and bookmarks for that!

Read the whole thing.

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Using the Power BI Visual Header Tooltip

Published 2019-07-29 by Kevin Feasel

Prathy Kamasani gives us several good uses of the Power BI visual header tooltip:

When we look at data journalism posts, most of the times they have annotations, explaining what visual showing or talking about measures. Again most of these data storeys are used for paper. But in the digital world, we do see these annotations more interactively. It is nice to have this kind of lil annotations for everyday reporting as well, and Tooltip Icon can be used for that purpose. Another thing is using canvas space wisely, it is important, and having this kind of hint helps us on saving the canvas space.

Click through for instructions on how to enable this as well as smart ways to use them.

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Equidistant Points and Missing Data in Excel

Published 2019-07-25 by Kevin Feasel

Stephanie Evergreen shows how you can bring in missing data points in Excel to ensure the axis is accurate:

Excel automatically spaces your intervals and labels equidistant from one another but it is assuming that your intervals actually are equidistant. In this graph, that’s not the case. We are missing the months of March, April, July, and August, when either no one was enrolled in the study or we have some missing data. But we can’t just gloss over those months. It isn’t truthful and it distorts the data display.

Click through for the solution.

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Bar Chart Presentation Options

Published 2019-07-18 by Kevin Feasel

Andy Kirk gives us five techniques for gussying up bar charts:

“Bar charts are boring”, say many people. “How can we make them more attractive”, say many desperate clients. Bar charts are ubiquitous because they are the reliable and trusted lieutenants often relied upon to show the always-common quantitative comparisons across different categories. Their frequent use can induce ‘boredom’ through the familiar but, in particular, accusations of inelegance can be raised with the default tool styles many creators lean on.

The five charts below just offer some different ways you might style them, through variations in the use of functional colour properties, chart apparatus and layout decisions, in particular. The reasons why you would choose to use any of these methods are varied and especially contextually dependent, based on matters like space to work in, range of quantitative values, size of category labels, number of bars, importance of precise readability. The charts are all showing the all-time top 10 most streamed songs on Spotify, as of July 2019, with data from wikipedia.

Read on for the five options.

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