They say your name defines you...what does the data say?
Everyone has a name. It’s what defines you and, as shallow as it may seem, it’s many people’s first impression of you. There is an entire industry of new baby preparation that revolve around choosing a name. And every name lives in a database within the Social Security administration and that’s what this dataset is all about.
Below are a handful of examples from the #DataFam community to help kickstart of ideas for you if are wanting to make a new viz! Click the image(s) to check out the interactive dashboard version!
I really like this first example from Liam Huffman. In it, he takes a look at the number of names with that particular first letter. I appreciate how quickly, you can see which letter was the most popular by size of the donut with the alphabet ring.
Inside the ring is a we get to see a bit more detail about the most popular name with that letter as a horizontal diverging bar chart.
Then down the left side of the viz, we see this nice trend line to show you total births by here. Throughout the dashboard, the interactivity is really nice. And since this was created relatively recently, Liam also added some really nice viz animation to further draw the user in.
Something I’ve really enjoyed about doing this series of deep dives is the discovery portion. With each dataset, there are examples I know I want to show.
But I always take some time with each dataset to explore Tableau Public for dashboards I’ve never seen and/or authors I’m not familiar with. And this example from 2018 is no exception as I don’t recall seeing this VOTD.
Published by Kasia Gasiewska-Holc, this is really cool dashboard with lots of fun elements that nicely blend data visualization and personalization. I really like how several of the annotations look like they’re hand drawn.
Kasia, clearly, has an eye for design. I appreciate how she separates the two sections of the dashboard with the off angled line. It helps your brain make the connection that “okay, something is changing” which can be very helpful to your audience but in a subconscious manner.
The heatmap in the bottom section while taking up a lot of space still tells a great story. That story is supported by some really nice annotations.
Let’s all take a moment to appreciate Tableau Story Points. Back in August of 2016, Eddie Hartman created this excellent story point dashboard with a collection of different views that all go together.
The first several views take a look at the generational trends among various names. For example, I like this first view here that shows the number of applications compared the number of unique names. And Eddie even references that insight in later pages. The last few pages of this presentation focuses on the popularity of various names in popular culture including music and tv. I also especially enjoyed the view that looked at the names of presidents. Very interesting
And lastly, for a bit of fun, he puts the user in the driver’s seat and allows for self discovery.
The next couple that I want to share are both by Tableau Public Featured Author, Zach Bowders. Zach is an excellent analytics designer and he shows off his skills each of these examples. I highly encourage you check out the fully interactive versions.
In “Happy Birthday” Zach put the end user in the drivers seat and lets them discover their own stories through the use of parameters and filters. Do you want to see how many girls are born with the name “Daniel” or how many boys there are with the name “Rachel?” Then this is the dashboard for you! For even more customization, you can even change the top level header to whatever you want. Want to send this to your parents on their anniversary? You can change the top header to whatever you want. Very cool!
Then, just recently, Zach returned to this dataset to produce an excellent story about the popular names of each of the last six (6) generations. This long form dashboard beautifully takes the users on a journey of popular names over time.
This viz earned Zach a well deserved VOTD honor. What I really like about this viz is how well Zach stays consistent with his design and how well he uses negative space. For example there are is a nice break between each generation which accomplishes two things 1) it provides a mental/visual break to reinforce the color change and 2) There just enough space there for Zach to put thin white border around the generation of interest. Please, do yourself a favor and click the picture to take in the full story. It’s worth it
These next two examples use a different version of the same dataset with the addition of US State added. If you are interested in this dataset, you can check it out here.
This first one is from Curtis Harris and was an #IronViz entry of his. One thing that I really enjoy is the interactivity. And I don’t just mean the Tableau actions, I mean he put the user in the driver’s seat. This is a dashboard that people will enjoy exploring more than once.
Aside from the interactivity, it’s a simple heat map that really tells a great story. The heat map allows the user to see the overall popularity of a name across the states. Then the reference line lets you see the popularity relative to a point in time.
Very cool stuff
And the last #DataFam example, I want to share in this post is from Bo McCready. I really like this US map small multiple map that shows the top names by state over time.
What’s really interesting to me is how quickly you start to see the number of distinct names increasing.
Another thing I enjoy about this dataset is the colors that pop which makes it easy to pick up patterns since each unique name is uniquely colored.
For example, you can very quickly see that Robert quickly starts to fade between 1950 and 1960 while Michael gets ready for 30 year run.
Then in the bottom right section, you can choose any year you would like e.g. like your birth year to see what map of names looked like then.
When you’re all finished with male names, your can flip the filter at the top and check out all the female names.
Excellent user engagement by Bo, here.