Last year in version 10.0 Tableau introduced the highlighter that lets us quickly highlight marks. It’s got two potential limitations, though:
We can only highlight a single value or all marks meeting a search criteria, not multi-select values.
Tableau’s Highlighter (and Highlight Actions) are hard-coded so we don’t have control over the formatting of the highlighted marks.
We can work around those limits in a few different ways:
Using a separate worksheet with Highlight Action(s) enabled with Hover or Select.
Using a separate worksheet with Highlight Action(s) enabled, a dual axis, and a duplicated dimension to display different marks. This technique was developed by Rody Zakovich in his post Only Color Marks on Dashboard Highlight .
Using a self-union’ed data source and a dual axis to get total control over how the highlighted marks are displayed and have more control over the user interface for choosing the highlighted marks. I think I might have invented this technique, I haven’t seen anything quite like it before. This method lets us build views like this:
Read on for how to build these out and choose the right method for you!
Since Tableau v9.0 or so every new release has come with new features that simplify and reduce the amount of data prep I have to do outside of Tableau. Pivot in version 9.0, the first batch of union support in v9.3, support for ad hoc groups in calculations, cross data source joins and filters in v10.0, and more in-database unions and join calculations in v10.2. With the join calculations we can now do unions and cross/cartesian joins within or across almost any data source without needing Custom SQL or linked databases and without waiting for Tableau to implement more union support, read on to learn how!
Here are some use cases for unions across data sources:
Union data that is coming from different systems, for example when different subsidiaries of an organization are using different databases but you want a single view of the company.
Union actual sales data from transactional systems and budget data that might come from an Excel spreadsheet.
Union customer & store/facility data sets so you can draw both on the same map.
This post goes through examples of all three using a combination of text files and superstore, and Rody Zakovich will be doing a post sometime soon on unions and joins with Tableau data extracts. (Did you know you could do cross data source joins to extracts? That capability came with v10.0, and we can have all sorts of fun with that using join calculations!)
We’ll talk about Sets in a bit, first we need to do a little forep discuss another one of the new features in Tableau v9.2: Min and Max for Booleans.
This post is the third in a series on new features in Tableau 9.2. It covers unannounced features in a version of Tableau that hasn’t been released yet so the features discussed here may change prior to release, especially if the folks at Tableau get a headache over my Sets puns.
In Tableau v9.1 and earlier we can only aggregate Boolean fields to do a Count or Count (Distinct). Here I’ve created a Xerox Flag calculated Boolean dimension with the formula CONTAINS([Item], 'Xerox') to identify all order items that include Xerox in the name:
Tableau 9.2 adds MIN(), MAX(), and ATTR() as aggregation options that have a number of impacts on what we can do in Tableau. Read on to find out!
New Aggregations for Booleans
Here’s the new context menu for a Boolean dimension in v9.2 using that same Xerox Flag showing Attribute, Minimum, and Maximum have been added:
To help show what the new aggregations do let’s start out with this screenshot with Customer Name and Xerox Flag as dimensions, in particular the three rows with blue Abc marks indicating there is data:
Aaron Davies Bruce (Bruce) who only has False as a value for Xerox Flag indicating that he has only purchased non-Xerox item(s).
Aaron Riggs (Riggs) who has both True and False, so he’s purchased both.
Alan Briggs (Briggs) who has only True, so he’s only purchased Xerox item(s).
If I aggregate Xerox Flag as MAX(Xerox Flag) then we see that:
Bruce has False because he has only the one value for Xerox Flag.
Riggs has only True, because the max of True and False is True.
Briggs has True because he has only the one value for Xerox Flag.
If I aggregate Xerox Flag as ATTR(Xerox Flag) then we see:
Bruce has False because he had only the one value for Xerox Flag.
Riggs has * because he has both True and False.
Briggs has True because he had only the one value for Xerox Flag.
What can we do with these new aggregations of booleans? Here are some ideas:
Filter by Discrete Aggregate
In an earlier Feature Geek post I’d described how in 9.2 we can filter by a discrete aggregate. We can put MAX(Xerox Flag) pill onto the Filters Shelf, filter for True, and boom we’ve got only those customers who have purchased one or more Xerox items–including Riggs and Briggs:
There is still one limitation here, we can’t drop ATTR(Xerox Flag) from a primary data source onto the Filters Shelf:
I suspect the reason why has to do with ATTR() being a special aggregation computed in Tableau whereas MIN(), MAX(), COUNT(), and COUNTD() are all computed in the data source.
However, when using data blending we can put ATTR(secondary dimension) on the Filters Shelf because of how data blending works – many aggregate filters on secondary sources are generally computed in Tableau, not in the data source, so Tableau already has that ability to filter on ATTR(secondary dimension). Here’s an example using Xerox Flag from a duplicated secondary source:
In v9.1 and earlier if we had a Boolean dimension and wanted to use it to create a cohort then we had to do an extra step that was often confusing to new users. For example if we want to only return Customers who have purchased a Xerox item we’d build a Conditional Filter using a By Formula: calculation like SUM(IF [Xerox Flag] THEN 1 ELSE 0 END) >= 1:
The inner IF statement is evaluated for every row and returns 1 or 0, then those results are summed up for each Customer and then if that aggregated result is >= 1 then the Customer is returned:
Having MAX() as an aggregation for a Boolean lets us get rid of the indirection of the SUM(IF… calculation and most of the typing as well since we can now specify the aggregation in the By Field: section of the view. All I had to do for this filter besides mouse clicks was type in “True”:
That is quite a bit easier to describe to new users!
Boolean Dimensions from Secondary Sources in the View
In v9.1 and earlier we couldn’t place Boolean dimensions from secondary sources in the view. Here in v9.1 I’ve duplicated Superstore and I’m trying to use the Xerox Flag from the secondary as a dimension and Tableau isn’t letting me drop it on Columns:
The reason why is that “under the hood” Tableau effectively treats dimensions from secondary sources as ATTR(dimension) — that’s why we get * for dimensions from secondary, see my 2014 Tableau Conference session on Extreme Data Blending for more details. In v9.1 and earlier Tableau does not support ATTR(boolean dimension) so we couldn’t drop the boolean. I already demonstrated above how we can use ATTR(secondary dimension) as a filter, and in v9.2 now we can directly use secondary boolean dimensions in the view, here’s the Xerox Flag boolean:
And we can use that Xerox Flag boolean dimension from the secondary as a filter:
Sets with Your Secondary (9.2 Style)
Awhile back I wrote a post on how to use Sets from secondary data sources. You see, ordinarily we can’t drag in a Set from a secondary data source, they are greyed out:
The workaround I’d come up with was a) to create a calculated dimension in the secondary source based on the Set that b) converted the boolean True/False of the Set into text or numbers that could be used as a dimension filter. For example this formula turns the Top N CC States Set from Coffee Chain into a calculated field of a usable data type:
And then the calc can be placed in the view, filtering for “In”:
Step b) was necessary because Tableau would not let us directly use a dimension with the Boolean data type from the secondary. With Tableau v9.2 we get a little closer to being able to have Sets w/out interruption use Sets more directly. We still need step a) convert the Set into a calculated dimension but we no longer need step b).
Here in v9.2 I’ve taken the Top N CC States Set and created a calculated Top N CC States Dimension field that has the formula [Top N CC States] so it’s just passing the boolean True/False into a calculated dimension:
And in v9.2 I can directly drop this calculated dimension as a filter:
So we can use Sets from secondary sources in v9.2 a little more easily than we could before.
Conclusion
Besides the big new features (Mapbox!!) Tableau continues to make iterative improvements in the ease of use of the software. Being able to aggregate booleans using MIN(), MAX(), and ATTR() just like we can other dimensions takes away the mental friction introduced by having to remember the data type every time we want to aggregate.
Tableau Public is running v9.2 already and you can see the aggregated booleans workbook and download it to your v9.2 beta. (If you’re not running the beta, you can get it by contacting your Tableau sales rep).
What’s New in Tableau 9.2?
Roughly two weeks after the public release of Tableau 9.2 I’ll be doing an online training on all the new features in Tableau 9.2 Desktop – this post is a sample of what you’ll be seeing in the course, a combination of how the feature works, where the edges are and how you might use it. Sign up below to get more info when the course is available!
This is the second in a series on new features in Tableau 9.2, if you’re really into this I’ll be doing a training on Tableau 9.2 a few weeks after the software is released, more information below!
A new feature in Tableau 9.2 is to make label colors similar to mark colors. Here’s the old way:
And the new:
To turn this on, check “Match Mark Color” in the Label Shelf->Font options:
In the scatterplot view above the mark colors and labels pretty much look like they match, but they aren’t quite exact. For legibility Tableau is applying an algorithm to alter the label color based on where the label is in relation to the mark. Here are some additional charts, notice how the Darjeeling label is a lighter green on a white background and a darker green when it’s over the light green Darjeeling mark:
The algorithm isn’t perfect, Chamomile & Decaf Irish Cream in particular are too light on the Area chart, there’s a bug with transparency and Area marks in the beta, and this is essentially v1.0 of this new feature so we can look forward to some improvements over time.
What’s it good for?
I regularly have line charts where there are a few reporting units with the group performance, this will help users make the connection between the labels and the lines.
Here’s the coloring labels workbook on Tableau Public so you can see it out for yourself, and download if you have the 9.2 beta (if you want it check with your Tableau sales rep).
What’s New in Tableau 9.2?
Roughly two weeks after the public release of Tableau 9.2 I’ll be doing an online training on all the new features in Tableau 9.2 Desktop – this post is a sample of what you’ll be seeing in the course, a combination of how the feature works, where the edges are and how you might use it. Sign up below to get more info when the course is available!
Tableau version 9.2 is getting close to release and thanks to a couple of little birdies — moles? informants? people whose initials are [redacted] and [redacted])? — I’ve learned about some features that weren’t announced during the keynote at the 2015 Tableau Conference. I asked for permission to talk about them and over the next few weeks I’ll blog about a few of my favorites.
NOTICE: This is a discussion of beta software and as such the described features and functionality are subject to change or complete removal prior to actual release. (Francois told me I’d get pie charts for Christmas if I didn’t put this warning here.)
The Problem
Up through v9.1 Tableau will happily put any continuous (green) pill on the Filters Shelf, but when it comes to discrete (blue) pills Tableau’s behavior has been inconsistent.
Discrete pills based on dimensions and record-level calculations like [Sales] > 10000 are supported.
Discrete pills based on regular aggregates such as SUM([Sales]) > 10000 have not been supported.
Discrete pills based on table calculations such as LOOKUP(SUM([Sales]) >10000, 0) are supported.
Here’s an example where I’m looking at Sales & Profit in my pirate-themed shops in New England. I’ve set up a KPI with the following formula:
IF SUM([Profit]) > 5000 THEN
"Thar be profit!"
ELSEIF SUM([Profit]) > 0 THEN
"Need more booty"
ELSE
"Arrr!"
END
In version 9.1 and earlier if I try to filter to see only the Arrr! circles to find the money-losing stores, I can’t drop the KPI pill onto the Filters Shelf:
There have been a few workarounds for this by:
Brushing/highlighting via the Color Legend.
Using a LOOKUP() calculation as described in the table calc section above.
Converting the discrete KPI into numbers that can be used as a continuous filter like IF SUM([Sales]) > 10000 THEN 1 ELSE 0 END, then filtering for 1.
Using FIXED Level of Detail expressions to convert the aggregate measure into a dimension.
This seemingly arbitrary distinction between dimensions, regular aggregate measures, and table calculations confuses new users and the solutions can cause further complications. It’s a point of friction that to us as users doesn’t seem like it needs to be there at all, no matter the underlying complexity of the problem.
Engage Friction Reducers!
In version 9.2 (with a little Mapbox Pirates theme goodness) this issue is gone, *poof* like it never existed:
So we users don’t have to keep in mind the distinction between calculation levels and pill types, we can filter away.
And the discrete aggregate pill is also completely usable as a quick filter:
…and can even be used as a scoped filter like continuous regular aggregate measures:
There is still one limitation here, we can’t drop ATTR(Xerox Flag) from a primary data source onto the Filters Shelf:
I suspect the reason why has to do with ATTR() being a special aggregation computed in Tableau whereas MIN(), MAX(), COUNT(), and COUNTD() are all computed in the data source.
However, when using data blending we can put ATTR(secondary dimension) on the Filters Shelf because of how data blending works – many aggregate filters on secondary sources are generally computed in Tableau, not in the data source, so Tableau already has that ability to filter on ATTR(secondary dimension). Here’s an example using Xerox Flag from a duplicated secondary source:
For me as a calculation writer this is a nice new feature because it lets me express KPIs and other measures in their natural forms and work with them more easily. As a trainer my students are less confused and can focus more. Thank you, Tableau devs!
Tableau Public is running v9.2 already and you can see the filter by discrete regular aggregates workbook and download it to your v9.2 beta. (If you’re not running the beta, you can get it by contacting your Tableau sales rep).
That is quite a bit easier to describe to new users!
And then the calc can be placed in the view, filtering for “In”:
