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  • Megan Johanson

Library Data Makeover: Using Color to Tell a Story

This interesting CNN article describes the New York Public Library’s most checked out books of all time. The article provides a list of the top ten books and their check-out numbers, as well as some insights on why some types of books were checked out more than others.


New York Public Library's top 10 most checked-out books.
New York Public Library's top 10 most checked-out books.


Visualizing the Data

While I think the data provided are really interesting, I don’t think the article does it justice. To really get the scale of the top ten books, I put them into a bar chart.


Doing so allowed me to quickly see that there was a difference of almost 300,000 check-outs between 1st place book and the 10th place book, which was not obvious when I viewed the list. That’s huge!


Standard bar chart of the library's top 10 most checked-out books.
Standard bar chart of the library's top 10 most checked-out books.


Using Color to Tell a Story

Once I had the basic bar chart, I realized that with a few very simple tweaks I could tell different stories with the same data.


Children's versus Adult Books

First, I color-coded the bars based on whether each book was for children or adults. As the article pointed out, children’s books are shorter and therefore do not take as long to read. This means that they are able to be returned and checked out more frequently than books for adults. Therefore, it was not surprising that children’s books made up six of the top ten.


By making all the non-children's book bars gray, they are visually backgrounded and the green bars draw your eye. Additionally, I added a subtitle that clearly states the main finding of this analysis.

Bar chart using color to emphasize the children's books on the list.
Bar chart using color to emphasize the children's books on the list.

Male versus Female Authors

Next, I wanted to tell a story about the authors of the top ten books. As you can see from the chart below, men dominate the list. The only woman to make the top ten was J.K. Rowling with Harry Potter and the Sorcerer’s Stone.

Bar chart using color to emphasize the only female author on the list.
Bar chart using color to emphasize the only female author on the list.

Fiction versus Non-Fiction Books

Lastly, I decided to color-code the data by fiction versus non-fiction books. The fact that there were so many children’s books on the list did foreshadow that there would be more fiction books than non-fiction, but I was surprised that even the books targeted to adults were primarily fiction. The one exception on the list is the business classic, How to Win Friends and Influence People.


Bar chart using color to emphasize the only non-fiction book on the list.
Bar chart using color to emphasize the only non-fiction book on the list.

Conclusion

Even a simple bar chart tells a powerful story that just can’t compare with the article’s original list. When I added targeted color into the mix you can see how easy it is to tell different stories with the same data set. Using color strategically guides the reader to your main point and certainly subtitles stating the main findings help.


Which chart was the most impactful for you? What story would you tell with the data?

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