Dataviz Attempt #1: To All The Books I've Read Before / by Charisse Tacang

I quit making New Year’s resolutions some time ago because I realized that celebrating the new year is a social construct in itself, and you don’t actually need to start doing new things or changing habits on January 1st for them to stick.

Over the years, I learned that if you want to make something happen for yourself, you just have to start. Whether it’s wanting to start a new diet, a new savings goal, or a new hobby — all you have to do is just start.

That said, I want to make it a habit to go back to making things for myself again this year.

I had been so caught up in trying to create for other people that I had forgotten what it was like to create for myself and for fun. My last personal project was Black Books and that turned out so much better than I had initially imagined (it’s a year old now!).

So this is me trying out something new again.

A few months back, I came across the work of information designers Giorgia Lupi and Stefanie Posavec in Dear Data, and more recently in the visual journal they came up with. I was fascinated by the different kinds of data they collected and the way they presented all that information in colorful and quirky illustrations. See their first project here.

Anyway, I thought I’d make use of my Information Design degree and try it out for myself.

I wanted to practice turning my data into drawings first, so I thought of using old information that I already had instead of tracking new things. This way, I also get to start immediately. Thankfully, my younger self thought it was cool to make lists of things I consumed at the time (e.g. books, tv shows, films, etc.) so it was easy to retrieve them. For my first attempt, I decided to visualize the data from all the books I read in 2011.

How I did it

In 2011, I made it a habit to list down every book I read and recorded all that information in my Goodreads account. Goodreads has a yearly reading challenge where you set a goal for yourself at the beginning of the year and you track your progress by adding books to your Finished Reading pile. That year alone, I managed to read 40 books (daming time), which is also the most I had read compared to the other challenges I did in 2012 (15) and 2013 (10).

Here’s a list of all the information I gathered from Goodreads based on my entries:

  • book title

  • author

  • book’s genre

  • whether the book I read was a physical or a digital copy

  • whether it’s part of a series

  • my rating for the book

  • book review

  • when I started reading and when I finished it

Other information I wanted to track:

  • if the book has a movie adaptation; if yes, did I watch it

  • if I read my own copy or borrowed it

  • if I still remember the book’s story today in 2019

I put them all together in a spreadsheet and studied the data from there. It took me a while to figure out how I wanted to illustrate some of the information, but I finally managed. Here’s what I came up with:

I am grateful to my 16-year-old self for making this list. Ang dami niyang time.

And here’s a cheat sheet on how to read it:

Some of my key insights from this dataset:

  • I read more books written by female authors. #thefuturereallyisfemale

  • Favorite genres at the time: fantasy and young adult (don’t judge, I was 16)

  • I liked reading books that were part of longer series.

  • Many of the books ended up being turned into movies, and these are the stories that I still remember today.

  • I read fast. Credit probably goes to all my free time during Chinese classes.

  • I borrowed most of the books (30) from friends and from the library. As a high school student with no source of income, I did not see the point of buying books when I could have access to them for free (by borrowing/downloading an ebook).

Where I want to go from here:

  • I would like to get back to reading more books again this year.

  • I would like to make more of these dataviz sets. My next project will be visualizing data from all the TV shows, movies, and music I consumed in 2018 (since I already have my lists).

Are you reading anything at the moment? Do you have a pile of books or other media that you want to track? Do you have dataviz projects that you want to share? Come yell about data with me!