The Chart Gallery 12/13: An interview with Advaith Venkatakrishnan

Posted by Maddie Hall on 12/13/19 1:56 PM

In collection, insights, Newsletter, The Chart Gallery, interview

Welcome to a special edition of The Chart Gallery! Every Friday we're highlighting members of the data viz community, their favorite projects and sources for inspiration. Today we're excited to introduce up-and-coming data viz superstar...


Advaith Venkatakrishnan!

 

Q & A

What do you want us to know about you?

Hey, I’m Advaith! I just recently started working as a Data Visualization Engineer for Blackboard Insurance. I am really fortunate to have turned my passion and hobby into a career. I like to focus on the experimental and create visualizations truly unique. I think we can benefit from experimental visualizations to see data in different ways against the traditional models. Currently I am designing a series of NFL and Fantasy Football visualizations that I hope to officially share soon!

What makes you passionate about data viz?

Data Viz to me is showcasing creativity with code and software. I graduated from Georgia Tech with a Bachelors in Computer Science in 2018. Straying from the traditional software engineering path, I wanted to go all in on data visualization combining what I know from code, art, and design. But I still have a lot to learn… that’s why joining Data Visualization Society and following a bunch of people on twitter is great way to see new techniques and ideas.

 

How long have you been creating data visualizations?

I’ve been creating visualizations on the side for almost 2 years now but 2019 was definitely the year I spent the most time actively cultivating my interest and exploring the depths of data viz. Looking forward to what the new year has in store for me!


 

Advaith's Creations

NFL Free Agency as a Node Network
d3.JS, Python, Pandas
2019
 

This is the first piece of work that I’ve made that I was fortunate enough to present at a DVS meetup. A node network to visualize free agency wasn’t something I saw done before and I knew I had to create it. The first iteration took about a week but over the course of a month and a half I tweaked my viz as I gathered more feedback from friends and helpful people on Reddit. I used d3js to create the graph and python to scrape the data.


What did you learn from creating the interactive?
The most important thing when creating complex visualizations is providing context and clear messaging to communicate to your audience. NFL fans got more value out of my viz when I took the time to highlight certain parts and explain my reasoning. For future visualizations I want to focus first on messaging so that I can make sure my audience is always on the same page and not overwhelmed.

What were some of the pain points in creating the piece?

The biggest pain point at the time was scraping two different NFL Free agency tracker sites. One had transitions data neatly organized in a table but data was a week behind. The other updated in near real time but wasn’t organized at all! Consolidating this information was difficult but important since the viz needed to showcase the most accurate landscape in NFL free agency.

 

Read more about how Advaith made this piece in The Nightingale!

 

Income Inequality and College Mobility
D3.JS, Python, Surge, Vue
2019

 

 There is definitely an advantage to being well off that helps when deciding which college to attend. And I wanted to see what the advantage looked like. The College Mobility Visualization uses a type of population pyramid structure to highlight college attendance in snapshots among different income tiers. The structure is ordered from most selective to least selective (top to bottom). A structure that is top heavy like in the 99% tier (individuals with parents with a very high income) means that more of those students attend selective schools like Ivys.

What did you learn from creating the interactive?
During this whole development process I picked up on better d3 practices and got better used to the selection and joins when changing data. I really like how the pyramids update when using the brush and legend slider!

What were some of the pain points in creating the piece?

The most challenging part during this process was trying to make this visualization mobile friendly. There were too many differences between I how I wanted this to look in mobile and desktop so I opted to punt mobile and really just focus on the desktop look and feel. On a monitor this visualization is really easy to use and highly interactive not so much on mobile.

 

North American Industry Employment Maps

d3.JS, colorbrewer2.org, Vue
2019

I honestly feel like this is one of my most well designed visualizations and really like how clean it looks and feels. I wanted to see which states employed the most people for a given industry (Construction, Manufacturing, Agriculture..etc). I chose my colors from a palette from colorbrewer2.org and used d3.js and Vue to create the small multiple maps.

Not only is this viz mobile friendly but it comes with a slick animation that sorts each state my median salary (click the play button). There weren’t too many pain points since the data was already cleaned and there aren’t too many complex interactions.

What did you learn from creating the interactive?
This viz taught me that I need to make more map visualizations because maps are too cool.

 

Advaith's Favorite Visualizations on the Web
 
 

How Kerala’s Dams Failed to Prevent Catastrophe by Reuters Graphics

I first saw this visualization while scrolling the Information is Beautiful nominees and really liked the way the story was told. The graphics of the dams were incredible and transitions between each story point seamless. For my next piece I might try to do something with WebGL in a journalistic manner like this.

 

NBA Tower Charts - Andrew Garcia Phillips


I’m a big fan of unique visualizations and really like how the NBA game charts tell succinct snapshots of each NBA game. I always look forward to seeing these snapshots for NBA games I missed on my twitter feed. I'm thinking about making a version for NFL games by next season.

Check out Advaith's Grafiti Collection!

That's all for today's edition of The Chart Gallery.

These charts and more are all available at Grafiti - the search engine for charts, graphs & data!

Email us at hi@grafiti.io with any questions, feedback and especially more charts.
Have a great week!
- The Grafiti Team