Book Club Wrapped

Turning our reading journey into data-driven insights

As an avid reader and data enthusiast, I found myself inspired to create a unique project for my book club - "Book Club Wrapped". This endeavor combines my passion for literature with my background in Data Science, resulting in an engaging way to analyze and present our collective reading experiences.

The Genesis

Our book club, born in the spring of 2020, has been meeting consistently every four weeks to discuss our latest reads. As we began rating and tracking the books, I saw an opportunity to dive deeper into our reading patterns and preferences. The idea of presenting this data as an annual "wrapped" report, similar to popular music streaming services, struck a chord with our group when I unveiled the initial results at the end of 2023.

Key Features and Insights

The heart of Book Club Wrapped is an interactive HTML document that offers a variety of deep-dives into our ratings and reading habits. Some of the intriguing questions we can now answer include:

  • Who tends to prefer shorter books?
  • Which members often vote similarly?
  • How do our individual tastes compare to the group average?
These insights not only provide entertainment but also spark discussions about our reading preferences and help us understand our literary journey as a group.

The Data Behind the Insights

At the core of Book Club Wrapped is a rich dataset that captures both our personal experiences and objective information about each book. After every discussion, each member provides a rating out of 5, reflecting their overall impression of the book post-conversation. This subjective data is then complemented by a variety of metadata for each title:

  • Number of pages
  • First publication year
  • Goodreads rating
  • Genre classification (non-fiction vs fiction)
  • Author gender
This combination of personal ratings and book metadata allows for multifaceted analysis. We can explore correlations between book length and member ratings, examine how our opinions compare to the broader Goodreads community, or investigate whether we have any conscious or unconscious biases towards certain types of authors or genres. The inclusion of publication years also enables us to track how our reading list spans different eras of literature. By collecting this diverse set of data points, Book Club Wrapped can provide insights that go beyond simple likes and dislikes, offering a more nuanced view of our reading habits and preferences.

Development Process and Technology Stack

To bring Book Club Wrapped to life, I leveraged my Data Science skills and chose a tech stack that would allow for both robust analysis and easy sharing:

  • RMarkdown: This powerful tool enables me to combine R code for data analysis with markdown for formatting, resulting in a polished HTML output.
  • GitHub: Actions I utilize this for hosting, ensuring our report is easily accessible to all book club members.

The Influence of Data Science and Previous Projects

My background in Data Science has been instrumental in shaping Book Club Wrapped. The skills I honed in data analysis and visualization have allowed me to create meaningful insights from our reading data. Additionally, my experience with the Route Planner app taught me valuable lessons about user experience and data presentation, which I've applied to make our book club report more engaging and intuitive.

Future Enhancements

While Book Club Wrapped is currently tailored for our group's use, I'm excited about its potential for growth. Some future enhancements I'm considering include:

  • Incorporating More Metadata: This will allow for deeper analysis of trends in genres, authors, and themes.
  • Predictive Modeling With: more data, I aim to build a linear model that could predict an individual's rating for a given book based on past preferences.

A Step in My Software Engineering Journey

Book Club Wrapped represents another step in my transition towards Software Engineering. By incorporating GitHub Actions, I've improved my skills in continuous integration and deployment. Looking ahead, I plan to enhance the project's front-end using JavaScript, aiming to create a more interactive and visually appealing experience.

In conclusion, Book Club Wrapped has been a rewarding project that combines my love for reading, data analysis, and software development. It's not just a tool for our book club; it's a testament to how personal projects can drive professional growth and bring joy to a community of friends united by their love of literature.

Written with the assistance of perplexity.ai.