Data Visualization



The basis for this report is to communicate visually the 2018 data set of the % of U.S. Adults who say they have read a book in the previous 12 months (more specifically print, electronic, or audio formats). Within the types and percentages of books read, the study breaks down people into six main demographics and identities within those demographics (ie. gender: men/women, race: White/Black/Hispanic, etc.). Looking broadly at the demographics, there are subtle and distinguishing differences among the identities. I would be curious to see how this data looks in other countries within the demographics provided as well as perhaps children in the age demographic, other race designations, and to an extent how many books they read not necessarily that they have read ‘a’ book. Each of these categories gives insight into niche marketing for organizations in reading/book industries plus educators – even though the youngest age group is 18-29.


In the United States (and potentially internationally), reading has been on a decline in addition to the format of print books in favor of digital books. Independent bookstores and some chains have been closing their doors or focusing their efforts on other products that lean into the digital age.  According to the Pew Research Center:

The same demographic traits that characterize non-book readers also often apply to those who have never been to a library. In a 2016 survey, we found that Hispanics, older adults, those living in households earning less than $30,000 and those who have a high school diploma or did not graduate from high school are the most likely to report they have never been to a public library.

Not only is reading on the decline, frequenting areas of public education and free resources are also decreasing for certain demographics. Efforts to make books more desirable, even as simple as accessible, should be the focus to increase reading overall as well as in specific formats. Looking at education and how reading/literature is taught and presented could impact this data visualization as assumptions are made for low socio-economic status, rural, and racially diverse individuals having lower literacy and reading rates.


The survey was conducted from January 3rd-10th, 2018 with a national sample of 2,002 adults living in the 50 states and D.C. The dataset listed below breaks down overarching demographics into sub-categories of identities. From there, the percentage of those identities who have read a book in any format followed by specifically a print book, electronic book, and audiobook. There are differences amongst the data across the board but the majority of large gaps occur when it comes to socio-economic status/salary, education level, and race. These gaps are consistent when looking at the format of the book as well. Not listed is that audiobooks have doubled from 2012 for adults in rural communities, high school graduates, and younger adults (18-29).


After posting the data set into RAW, a treemap seemed the best approach to convey the groupings of main demographics and then breaking them down into their respective sub-categories. To show the relationship within each of this main demographics, an analogous color scheme was implemented in the six main blocks to denote similarities yet slight differences. The typography chosen pulls from the traditional script used on older book spines. The type denotes the sub-categories within the main demographic as listed above. The added complementary color rectangles serve as elements of a hardback book spine adding depth and texture. The thickness of each block represents the percentage of individuals who read a book in any format – the thicker the block, the higher the percentage compared to its counterparts in the same groupings. What is not depicted is the formats of which the books were read as these were consistent with the overall trend of reading a book in any format.

Design – trends, specific points, outliers

Looking at the data visualization, an interested client/business could confirm the markets that they are hitting consistently. Women are more likely to read a book than men, white more so than diverse races, and graduates from institutes of higher education more. I would challenge industries/educators to see how close some of the other categories are and to strive to have more balanced markets. What was surprising was that in the Age demographics, 18 to 29-year-olds are leading the pack as the youngest age group surveyed. Seeing that today’s younger generations (Millennials) are seeking more opportunities to advance could be the rationale for the gap. It breaks a potential stereotype of Baby Boomers and older having more time to read after retirement – additionally, the assumption that younger generations do not read as much as they should. There is a fair balance within the salary category until $30,000 and below. Looking closely, $75000 has the slight majority compared to the middle classes of earnings. Overall, the visualization confirms areas of privilege leading to being able or wanting to read.


For further research in this data visualization, I would like to see a longitudinal study as this was this current year with input from 2012. I am also imagining a heat map of sorts with the United States since there was a fairly even distribution in areas of residence in the U.S. but to see it across the map with which states/cities could be eye-opening. It is unfortunate that some of the demographics are narrow, such as the gender binary and race being represented in three areas. A future study could expand on those identities. With the information we have currently, I wonder if organizations in the reading/book industry could adjust marketing, outreach, and accessibility tactics to engage populations who are falling with reading every year, regardless of format. Incorporating the latter of formats, listening to podcasts has been on the rise, so how can companies make audio books in the style of podcasts might drive more traffic to audiobooks – some listeners (readers) are able to multi-task with this format, also binging (podcast) “episodes” like Netflix and Hulu.