Introducing the "Change plot"

A common issue I've seen is how to visually represent percentage change and current values for a high number of categories at the same time. To solve for this, I created a new chart type called the "Change plot." 

Read and click through the Tableau story below to learn more about it. Click on the far right of the Tableau toolbar to view in full screen. Another new chart type I invented is the Polyarea chart, which you can read about here.

The Future of Government

The 2019 World Government Summit has partnered with Information is Beautiful to create the World Data Visualization Prize. The competition involves creating data visualizations based on one of three provided concepts and datasets.

I submitted a data visualization that explores "The Future of Government." Click here to access the interactive version: http://bl.ocks.org/akatona1/raw/1daa312799d7a438d2a45420e5fe01a8/

See the video below that demonstrates how to interact with the visualization. For more D3.js work, check out my Polyarea chart that was featured by Kantar at the Information is Beautiful Awards.

The code used to create this visualization is available on GitHub: https://github.com/akatona1/WDVP_The_Future_of_Govt

Top 101 data visualizations worldwide for 2018 Kantar IIB Awards

In an effort to innovate within the field of data visualization, I created a new chart type called the Polyarea chart. I entered this work to the 2018 Kantar Information is Beautiful Awards.

On 12/4/18, I attended the awards ceremony in New York City. Even though I didn't win, I'm honored that my work made the top 101 visualizations worldwide for 2018 and was displayed next to work by FiveThirtyEight, Bloomberg, Reuters, The Guardian, National Geographic, The Economist, Harvard, and many others.

See a video of my work being introduced and photos from the event below. If you'd like to build the chart yourself, I've created posts for D3.js and Tableau. 

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Attending the awards ceremony for the Kantar Information is Beautiful Awards in New York City #iibawards #nyc #newyorkcity #d3js #datascience #datavisualization #dataviz #visualization

A post shared by Alex Katona (@alexkatona1) on Dec 13, 2018 at 8:56pm PST

Polyarea chart using D3.js

(Click the gif above to view more easily). For the code used to create this visualization, here is the link to the GitHub repo: 

https://github.com/akatona1/Polyarea-chart

To interact with the visualization on your laptop, you can download the files from the GitHub repo. Then, place the files in a directory, start a local server (e.g. using the command "python -m http.server" from an Anaconda prompt), go to http://localhost:8000/ from Chrome, and click on the "Polyarea_html_Alex_Katona.html" file.

I submitted this work to the 2018 Kantar Information is Beautiful awards and it is now displayed on their site: https://www.informationisbeautifulawards.com/showcase/2996-polyarea-chart. Polyarea charts can also be created in Tableau. 

Best of Marketing Dashboards by Tableau

Tableau compiled the best presentations of marketing dashboards from their customers and the dashboards that Tony Valeriano and I created for our Tableau Conference 2017 presentation made the list! 

This was announced in Tableau’s newsletter that was sent on 8/14/18. Our presentation is the first one listed under the Analyst section. You can watch the presentation on Tableau's website or embedded below. There are photos from the presentation on this post. 

Popping Parameters for Tableau 10.4 and above

My Next Level Popping Parameter blog posts have been very popular. However, Tableau has made changes to the software which broke the method that was used to create the functionality for the Part 1 post. For Tableau versions 10.4 and above, it requires a new method of creating popping parameters that is described below. For this post, I'm using Tableau Public 2018.2.

Tableau Conference sessions now available on YouTube

The Tableau Conference sessions where my work was presented are now available on YouTube. There are photos from the 2017 presentation on this post. 

2017 session where I presented titled “Macy’s: Cracking the code of A/B testing and market basket analysis”:




2015 session that my manager presented titled “Making Data Visualization Actionable at Macy's”:

Tableau Conference 2017 Presentation

Thanks to everyone that attended my presentation at the Tableau Conference 2017 and watched online The presentation is now available on YouTube and the dashboards in this presentation were selected by Tableau as some of the Best of Marketing Dashboards across all of their customers! 

I included some pictures below (click to expand):

Building and modifying Tufte boxplots in R

In this post, I included an example of how to build and modify Tufte boxplots in R. The data is from DataSF through the open data initiative and relates to SF Police Department crime incidents. Here is what the final product looks like (click the image to increase the size):

For more unique data visualizations, checkout out my posts on the Polyarea chart and Change plot. 

How to create a Polyarea chart

I was interested in displaying the percent of total for many categories over time. However, I didn’t want to use a stacked bar chart or stacked area chart. This is primarily because it can be difficult to determine if the categories in the middle of these charts are increasing or decreasing over time since there is no common baseline. I created a new way to visualize this data in Tableau that combines many area charts (hence the name Polyarea chart). This can be built in less than a few minutes. This chart has been internationally recognized and can also be created using D3.js. 

Using embedded extracts to edit published data sources on Tableau Server

There are advantages to using a published data source, but there is one downside to using them. As mentioned in this link, it is not possible to edit a published data source directly on Tableau Server and requires that the developer make a local copy of the data source. The method described in the link is not ideal for the following reasons:

Response to specific date functionality question

I've received some great feedback from the Tableau community regarding my blog post about How to default your Tableau dashboard to yesterday (quadrupled my Total Site Pageviews!) so I thought I would answer a question that I received on Linkedin about a specific date functionality: 

Next Level Popping Parameters, Part 2

This is Part 2 of the Next Level Popping Parameters series. Part 1 of this series describes how to make horizontal Next Level Popping Parameters and Part 2 describes how to make them vertically. The methods that I’ve developed build upon the work that has been done by The Information Lab involving Popping Parameters.

Next Level Popping Parameters, Part 1

Before we get started, I thought it would be good to answer the following question: What are popping parameters and why should you use them? "Popping Parameters" is a term created by The Information Lab that refers to the idea of limiting what parameters are displayed to the user based on what the user has selected.

How to default your Tableau dashboard to yesterday

A common request when building a Tableau dashboard is to have the dashboard default to a specific time frame (e.g. yesterday or the last 7 days), but also allow for the ability to select a custom date range. This post focuses on how to build this functionality.