These are slight variations from Ryan Sleeper's blog and Andy Kriebel's blog on designing donut chart. Please refer to Andy's blog for the step-by-step tutorial.

By making part of the circle white, it shows a stronger contrast between actual and distance-to-goal.



Example 1: Donut with border
This recreates exactly Ryan Sleeper's design without using a jpeg picture. To make the border appear, you need to click the color mark, and select the border of interest. Note that we need to add border to both outer and inner pie charts.




Example 2: Partial donut 
Without border, the partial donut looks quite interesting. It stresses on the incompleteness of the progress. It's up to you which variation is of interest to you.

To make "Left-to-goal" in white, we need white color in color palette. There is no such color in default Tableau's collection of color palettes. We have to make a custom palette with white color. The trick is to include this code snippet

<?xml version='1.0'?>

<workbook>
<preferences>
<color-palette name="Pure White" type="regular" >
<color>#FFFFFF</color>
</color-palette>
</preferences>
</workbook>

in this preferences file:
C:\Users\<username>\Documents\My Tableau Repository\Preferences.tps

Then we can assign the white color to "Left-to-goal" and make it white.

The Viz on Turing Award winners just got selected as the Viz of the Day on Dec 19, 2014.

This is a nice little Christmas gift. Big thanks to the Tableau community and those who nominated it!

Wish everyone a great Christmas and happy new year!

[Updated on 6/15/2021. Click image below to go to the interactive version. Feel free to download the workbook.]

Recently I came upon a summary about Turing award winners published in 2008 by a friend of mine, Huailin Chen, who maintains a blog about computation (in Chinese) http://www.valleytalk.orgThis inspired me to build this dashboard to put all the award winners in a single page along with a bit of stats. Above is the result. This has nothing to do with the latest movie: The Imitation Game. Yet to watch it.

By Birth Country
USA leads in the birthplace rank with 38 natives among 61 laureates. None of the laureates are born in the Southern Hemisphere, although 2 are born at places as south as Venezuela and Sri Lanka.

By Gender
3 women made the list which is largely dominated by men with a count of 58 or 95%.

By Age
2 won the awards at the tender age of 36 and 38: Donald Knuth (1974) and Robert Tarjan (1986).

The award winners' age is trending higher. In 1980, the projected age is 50 and in 1998, it's 60. In 2016, the forecast shows that future laureates will be around 70. The award age increases 10 every 18 years. This signifies that the computing field is getting more mature each year. The major breakthroughs in theory and practices seem to have been made many years ago. But, personally, I believe that the latest development in large scale web computing technology by the younger generation is within the scope of the award. People like Linus Torvalds could make a great candidate for the award. His contributions to the development of Linux, to the open sourced software development weigh immensely in the history of computing.

By Zodiac Sign
Half jokingly, my friend Nick and I talked about using Zodiac sign as a dimension in the analysis of personalities. In some cases, we do find significant biases in the distribution such as in Turing Award winners. 1 in 6 are Capricorns while only 1 in 30 are Scorpios. Does this mean that Capricorns are 5 times more likely to win Turing Award than Scorpios. I am not in a position to interpret it and will leave it to astrology experts.

To be continued
Will discuss some of the intricacies in the design of this dashboard in another blog.

My colleague Sandeep came over to tell me how marvelous a little trick I told him the other day is: copy and paste. Sandeep is an experienced Tableau designer and he has designed a few sophisticated dashboards. If he didn't know it, I thought it might be worthwhile to write it down. It's probably one of the least known productivity tricks in Tableau. 

Import data fast

By Control-C and Control-V, one can minimize the time spent on data importing, data scaffolding and accelerate prototyping. 

One can copy data from anywhere (such as Excel, Web, Notepad ...) and paste it into a blank worksheet. Tableau will take the data in tabular form while expecting the first row to be the column names. Data in Notepad are expected to be comma separated or having other delimiters.

Web Scraping

Web scraping is easier than ever. Any curious soul can try to import the data from this web page, into a Tableau worksheet, by copy and paste.

There are 2 data tables in this page:
http://www.premierleague.com/en-gb/news/news/2013-14/may/premier-league-broadcasting-commercial-payments.html

You can try to copy both tables into Tableau worksheets. You might have problem with the first table. [submitted a ticket to Tableau under case number 01117583] Its format may not be recognizable completely by Tableau. One of the rows is not correct. My solution is to paste the data to Excel first, then copy it and paste it to Tableau. Excel has a stronger capability to recognize web data tables than Tableau does. Hope that Tableau can catch up and save us a trip to Excel.

This way, we can do a quick analysis of any data we see on the web.

Build glue table

In an earlier post on Funnel Chart, I needed to build a glue table to bring data of different sources into a 4 phased table. Then I can build a funnel chart with dynamic data. Before this, we were looking for a way to union data and didn't find any solution.

To build the glue table, I typed 5 lines in a Notepad window:

Phase
Visits
Leads
Opportunities
Funded

Then pasted them into a Tableau worksheet. Now I got a single dimension Phase with 4 values, from which I built a glue table using calculated field, providing the formatted data to feed the funnel chart.

Create dynamic document