As you probably already know if you have followed some of my content over the past couple of years, I am pretty excited about the release of the Extensions API for Tableau. This blog is an overdue follow up from #TC18, where Tamás Földi and I presented on Extensions, demoing a number of extensions covering both advanced visualization types and capabilities (like write back). This post provides some of my own perspectives on Extensions in Tableau as well as the content presented during TC18, along with some new stuff.Read More
… We are going to be integrating with and leveraging Nivo, which is self described by Raphaël Benitte (it's creator) as “supercharged React components to easily build dataviz apps, it's built on top of d3.” Nivo is one of many react component libraries that work on top of D3, each are different and bring their own features and focus to their projects. Here are a few more worth checking out (in no particular order):
I am going to assume you know how to leverage create-react-app and npm install to get up and running locally and import all the component libraries you will need. If you have not gone through this install process yet Chris’ blog walks you through some key steps you will need to complete, and Google is of course your best friend here. Here are the commands to run:
Npm install tableau-api
Npm install nivo
That is it, if you run npm start at this point, your project will be bundled and rendered locally on your machine... Magic!Read More
Previously I wrote this post around analyzing the predictions generated by 538 during March Madness each year. At the end of the post, I briefly discuss the possibility of telling the same story using animation in place of vertically scrolling through a static set of charts. I believe that, if used correctly, the ability to animate from one chart to the next can greatly assist the reader in understanding your analysis process.Read More
This post is a follow up to my Vizception post from a few months back. We are still building off the technique described in detail within that effort. Here we will look at two additional implementations leveraging the capabilities available within d3.js (thank you Mike Bostock!).
The first of the two implementations looks at leveraging d3.js mapping projections. Tamas Foldi and I presented this example during a recent Think Data Thursday. Here we will leverage the referenced d3.js code and adapt it for use with our Tableau integration method. This will allow us to build choropleth maps in Tableau with access to the d3 projection library which provides just a few more options in addition to your standard Web Mercator (the Tableau default).Read More
We wanted to show a real example of how to bring more to Tableau Server without additional hardware or hosting needed. That’s right, no additional server purchase requisition requests needed. There are really too many use cases to count when it comes to this, the details herein are only the tip of the iceberg.
We had a few short discussions and landed on the following example. This includes not only native d3.js integration but also an example of viz in a viz (in a viz) on Tableau Server. As a starting point, we used the twitter network graphs that Keith Helfrich and I recently shared, which were showcased on the Tableau bloglast month.Read More
As I embarked on this journey a while back, I had some goals when it came to what I was looking to build. These are summarized in the below bullets.
- Visualize Twitter network growth in detail using some form of network graph
- Needed the network graph for each year to be comparable to one another
- Interactivity against the network graphs was a must
- Provide a way for the user to view the actual tweets
- Once Keith and I decided to run parallel with our efforts, we wanted to way to “jump” from one view to the other.
The sections below detail out how I went about trying to achieve each of these goals. Don’t ask me why I gave myself so many of them.Read More