As a Computer Science professor for 20+ years, I know that data on its own can be dry and difficult to interpret.
As data professionals, we all know that data can tell a story far beyond the numbers, but how can we tell that story well?
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Everyone loves a great data visualization that tells an interesting story.
To connect our audience with the data as information and make it relatable, memorable, and impactful — this is pure gold.
Here are 8 examples where I believe this has been accomplished with great success!
The Cost of Christmas!
Apparently, Canadians take their Christmas celebrations very seriously. The choice of bar graph is spot on — it represents a Christmas tree.
The green bar correlates to the green branches of a Christmas tree. The flags of each country also kind of act as “decorations”.
What is unexpected in this story? I didn’t know that folks from Canada (or Lebanon?) spent so much on Christmas celebrations.
Fun, colourful, and very informative.
Peak Relationship Breakup Times During theYear
A perfect example of where annotations work brilliantly to highlight particular data points, this chart uses a time-series line chart to show the volume of relationship breakups during certain times of the year.
This data is from the US — more specifically status changes and posts scraped from Facebook.
It is interesting that “Spring Break” is the highest — this is when people traditionally do “spring cleaning”. It seems that the same may ring true for for relationships.
Other interesting dates during the year:
Monday is the most common day of the week to break up (maybe the weekend didn’t go well?)
People don’t want to be “tied down” during summer vacation (maybe heading off to college in September?).
It’s very “bad form” to break up on Christmas Day.
Nathan Yau’s “Stages of Relationships”
Nathan Yao does a brilliant job of showing data in motion. His site flowingdata.com is a treasure trove of examples like this one. This example shows relationship progression (over time) from first meeting to marriage.
Each dot represents a person, a colour the relationship phase that each person is in. The chart represents 1000 “average” people. The animation on the left is the timeline for relationship progression in the 1970s. The time on the right is the progression in the 2010s.
An interesting story that this graphic tells us is that with modern relationships people are slower at progressing, and are less likely to actually tie the knot (get married) — at least for the 15 years represented in this animation.
NASA’s Perpetual Oceans
This is an absolutely amazing data visualization that contains not a single word. It is part of a set of visual animations created by NASA.
These animations show global ocean currents by using line thickness and direction to indicate prevailing currents.
200 Years of United States Immigration
Immigration in to the USA over the past 200 years has gone through many changes and phases — in volume and in origin of nationality.
This is represented in brilliant color and detail in this data visualization representation, called an alluvial chart:
In this diagram, we can clearly see the story of the Immigration Act of 1924. This legislation completely excluded immigrants from Asia and severely limited the number of immigrants of other nationalities.
And when the restrictions were finally relaxed, the origin and makeup of the new immigration population had significantly changed.
How Long For a Hacker To Brute Force a Password?
Sometimes, when we need to show a lot of data points, the right choice is to show the data in a table — this is a good example where a table is the right choice for this amount of data.
The graphs show the time taken to hack a password based on the complexity type. Lots of colors can blur the meaning but this graph uses the right conditional color formatting to depict the time taken to hack the passwords.
Red and purple indicate danger areas — green indicates the “safe zone”.
The story here? Don’t be a statistic — use complex passwords with a combination of characters.
2023 Search Trends — Ridgeline Plot
This particular data visualization is called a “ridgeline plot” and is used to summarize the distribution of numerical values for a group of fields.
In this example, each ridgeline represents how often a particular topic was searched for over the time line of a year — in this visualization, for 2023.
On the x-axis, you can see that this is a timeline starting in January of 2023 until end of Dec 2023 and it gives a great idea of some of the most searched topics on the internet in 2023.
And Lastly… The Top 50 Visited Websites in2022
This one has definitely made the rounds on the internet so you may have seen it before. It is terrific in that it uses bubbles by size to show volume of traffic, and color to show the category of website.
It is no surprise that Google is at the top of the charts here, followed by YouTube and Facebook. What is noticeably missing here is the volume for Netflix, and also for OpenAI. OpenAI received 2B users and Netflix 1.55B in December alone (according to semrush.com).
The next iteration of this chart will reflect these changing patterns in Internet usage.
Estimates are that there are more than 2 billion websites that are accessible over the internet, with a large proportion of these receiving little to no traffic at all.
To Summarize…
There are many interesting and little-known visualization techniques that can be used to tell great stories about your data.
Hopefully this interesting slice of visualizations using various methods of display — from animated imagery, to bar charts, to bubble charts, to alluvial charts, to ridge line plots — has expanded your repertoire.
And that you feel inspired and motivated to use some of these example styles in your own data visualization masterpieces!
Thank you for reading!
Data at Depth is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.
