Jupyter notebook was used to generates visual representation to a user's library as it was exported from Goodreads. Below are the results of my personal library.
You can use it with your own data - go to https://www.goodreads.com/review/import and press "Export your library" to get your own csv.
To get the interactive version. Replace the path to my Goodreads exported file by yours in the ipynb file or over-write over the CSV with the same file name.
https://s14a-final-project.herokuapp.com/
Below are some ofthe python packages that will be required.
seaborn
pandas
wordcloud
nltk
distance
image (PIL inside python for some weird reason)
gender_guesser
rpy2
The relationships of interest to be visualized are currently:
- plot Pages vs Ratings
- plot Ratings vs Bookshelves
- Plot books read by year
- plot Heatmap of dates read
- plot Word Cloud
More to come in the future!
- Thanks to Jeff Baglioni for providing guidance