Welcome!

I have uploaded notebooks of a few qunatitative finance related projects I have done recently. You can find them in this repo. The readme contains detailed summaries of each projects, so I won’t write a blog post for each one.

I made a Python Panel dashboard for Letterboxd. This dashboard resembles the stats page included in the Pro subscription. The visualizations are interactive. When you hover over the bars, a popup displays more information (such as the counts, etc.). If I find the time, I will host it on Heroku or somewhere else. But for now, if you would like to run it on your own (with your own scraped data), check out the app code here....

In this post, I will make a Letterboxd scrapper. In case you didn’t know, Letterboxd is a film logging site with built-in social networking features. It is a great platform, but the company does not provide a public API for their data, so one has to use a scaper to get their hands on the film/user data. For this scraper, given a username, we want all the films the user has logged....

This is a follow up post to Part I of How to make and host a Discord Bot where I go through the steps to make a simple bot using the discord.py library. In this post, I will conclude the tutorial by explaining how we can host the bot we made in part I. Hosting the Bot We will host the bot on Amazon AWS. Amazon offers a basic plan on EC2 (Elastic Compute Cloud) free for a year!...

I have found out that it takes a lot of time porting big Jupyter notebooks to a markdown document; sure, Jupyter can do that for you, but tweaking the markdown document so that codes and tables match the style of your blog takes an unecessary amount of time. It takes even more time to explore the data and derive insights from visualizations. Now, this is a necessary task. That’s why for the remaining journey of this Quora Challenge, I will be posting cleaned IPython notebooks along with a short summary of what I did in there....