I like to read. Like a LOT. But I’m not limited to just books. I read everything that comes my way – books, articles, Reddit threads, tweets and what not. Consuming information by audio (podcasts, audio books) or video is just not my thing. Text is how I like it – and to keep track of all the articles and posts I have to read (but can’t at the moment), I use a very popular app called Pocket. Whenever I come across any interesting article that needs to be saved for reading later, I just save it to my Pocket account. It’s a very handy app – you can save articles from your phone, within apps or from your browser. You can then go back to it later and read the articles in a distraction-free way, offline.
Being the data-curious person that I am, I thought, why not use data analysis to gain deeper insights on my internet reading habits using my Pocket data? So this is what this post is about – I explore trends on how frequently I add articles to my Pocket, how frequently I read them and what those articles are about. I use the Pocket API and Python language to do this analysis. Let’s go!