Recently I created a tabular report where it was a requirement for the user to be able to sort the list by all of the different measure columns. I generally publish my reports on to Tableau Server where sorting is easy by using the Tableau toolbar but I wanted to see how to do this without using the toolbar.

I began to think about ways to do this using parameters and calculated fields as a Dimension has the option of Sort By Field. Luckily I didn’t have to think to hard about how to do this as I stumbled across a blog post which describes how to set up dynamic sorting with Tableau. I slightly modified the more complicated of the 2 techniques described in that article, which I describe here.

For this example I’m going to use the Superstore Sales sample data Tableau provide and create a table showing the Customer State on the rows and the measure values Profit, Profit Ratio and Sales in the columns. If unsure how to do this check my other post on displaying data in tableau as a table. Read more…

Displaying measures in a table in Tableau is something that should be straightforward but for some reason I always struggle with it hence I’m writing this blog post. In the Tableau screen at the bottom of the Dimensions section there’s a field called *Measure Names* and in the Measures section there’s a field called *Measure Values.* These are the 2 fields that make life easier when displaying data in a table. Read more…

This post about how to create bins from a measure in Tableau was originally written in the days of Tableau 7. Now things have evolved and it is far more straightforward, the updated article on using LOD calculations to create bins from a measure is here.

For this post I have to give a huge thanks to Richard Leeke who found the ‘Tableau only’ solution (as opposed to pre calculating the data) for this problem. As a quick overview for what I was trying to do using Tableau, I wanted to create a calculated field of which the result would be used to create bins. The calculated field is a measure, not a dimension, but the same rules apply.

The post is quite long and complex hence it’s broken up into multiple parts – the solution using data blending will be detailed in the next post, creating bins from a calculated field.

The test data has 3 columns: Month, ListingID and EnquiryCount – in other words it showed the enquiry count per listing per month. I wanted to calculate enquiries per listing over the entire time period and use the result of this calculation for the bins. The sum of these enquiries for each listing id defines which group they belong to – i.e. 1 – 10, 11 – 20, etc. In other words if ListingId 1 had an EnquiryCount of 10 in Month 1, 2 in Month 2 and 8 in Month 3, ListingId 1 received 20 enquiries in total so would be in the bin 11-20. Once I know which bin each listing belongs to I want to see for each group what % of total enquiries came in month 1, month 2 and month 3. For ListingId 1 50% of enquiries were received in Month 1, 10% in Month 2 and 40% in Month 3. Read more…