Introduction

The topic that I chose for this Tableau Public lab is ‘NYC Leading Causes of Death’ — As dark as this sounds, epidemiology has been one of the topics that I have been interested in but never really got a chance to delve into. This assignment is my first attempt at visualizing factors related to health and possible control of diseases by gender in NYC.

Materials

The primary software used to create this visualization is Tableau Public. It is a free software that can allow anyone to connect to a spreadsheet or file and create interactive data visualizations for the web.

In terms of data, it is sourced from NYC Open Data which is an open-source platform that generates data through various New York City agencies and other City organizations available for public use. As part of an initiative to improve the accessibility, transparency, and accountability of City government, this catalog offers access to a repository of government-produced, machine-readable data sets.

Another possible tool that could’ve been used for this viz is OpenRefine. Formerly Google Refine, it is a powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data. However, the data I sourced was clean enough to plug into Tableau Public without any issues.

Methods

Tableau Public is a free service that lets anyone publish interactive data visualizations to the web. Visualizations are created in the accompanying app Tableau Desktop Public Edition (or another Edition of Tableau Desktop) – no programming skills are required. However, understanding of data and what the tool does is important to learn.

Compared to Timeline JS, this tool definitely has a higher learning curve and took me more time to get acquainted to. Since this software is for anyone interested in understanding data and sharing those findings as data visualizations be it journalists, writers, bloggers, students, professors, or hobbyists there is a comprehensive list of tutorials and training options available. This is where I started.

Starting with a set of video tutorials, I learnt the basics of Tableau Public. After that I progressed on to trying a random dataset and got even more familiar with the software.

Since I am not from a data background, I mostly struggled with understanding what Tableau was capable of. I had trouble with deciding what exactly I wanted to visualize and what was the purpose of it.

Once I finalized a dataset, I tried to tell a story. My main aim was to visualize the dataset in a way that it gave a comparative analysis of different diseases affecting men and women and at what rate. The purpose of this viz is to educate people about different causes of death and how they are affecting different genders.

Results/Discussion

The visualization can be viewed here.

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I presented three visualizations on compiled them on a dashboard on Tableau. The first one gives a high level summary of death rates per gender. The second one goes in a little deeper and has a heat map like format where is gives number of deaths affecting per ethnicity per gender.

The third one is more interactive as it gives the users a chance to navigate through each leading cause of death and in a graph like format presents how it affects each gender per ethnicity in NYC. The users can compare death causes on both the axis.

I played around with the formatting as well and used different kinds of filters and colors to make the visualization most impactful.

Placing all the visualizations in one dashboard where I was not sure about the size was a little disorienting because I had to deal with a lot of re-editing and color correction for my visualizations. But overall, once they came together, after correcting the sizing and the colors they looked fine together and told a story.

Working on Tableau Public was a pleasant experience overall. It is a great tool for creating visualizations and I love the level of interactivity and responsiveness provided for the data. I did take some time to get used to it and get comfortable with data and how it can be presented but that could also be because of my lack of experience with it.

Further Directions

If gotten a chance, I would’ve loved to clean messy data on OpenRefine, so for the next time I would choose a complex dataset. Other than that, I noticed more variations and sizes on the dashboard and I would love to work with them and set up my sheets accordingly.

Furthermore, I would like to clean my visualizations and make them more understandable and cleaner via advanced formatting.

Overall, Tableau Public was a fun platform to work on and by creating more and more vizs and practice I can get better and add more interactivity and usability to this visualization.