Where Data Meets Curiosity
In a nutshell, I share my code and thoughts while replicating data and reverse engineering data visualizations that I find interesting online, mostly data-driven news articles along with analyses I like to do in my spare time.
You will also find external links to more of my work in the ‘Older Links’ section.
Feel free to connect with me if you have any questions or suggestions !
List of Projects
Is NHS Good Value?
Replication of a data-driven article and analysis of the UK’s healthcare systems among other countries; by British editor Tom Calver. This study compares healthcare efficiency metrics across multiple nations.
Stock Market Analysis & Forecast
Comprehensive analysis of stock market trends and predictive modeling using Python. This project examines market patterns and develops forecasting models for investment decision-making.
Has Int. Travel to the U.S declined?
Replication of a data-driven article/analysis of the impact (if any) of President Trump and his administration on international tourism into the United States; by Josh Holder et. al. Examining tourism trends and policy effects.
Cool looking Inversions
Here I explore some ways to draw cool looking objects, namely using inversions - inspired by Micmaths. Creating geometric art through mathematical transformations and exploring the beauty of inverse geometry.
Koch and his Snowflake Fractals
Here I explore some ways to draw cool looking objects, here snowflakes namely using fractals and their properties - inspired by Micmaths. Diving deep into recursive patterns and self-similar structures.
The state of Journalism in Gaza
Replication of ACLED Visual (Armed Conflict Location and Event Data) where the data looks at casualties among journalists since October 2023 through to end of August 2025. A critical examination of press freedom and safety.
The 9/11 Legacy
Replication of a PEW Research Center where the data looks at, among other things, the emotional toll of 9/11, its enduring legacy, and its polarizing impact on the Political Spectrum. Analyzing long-term societal effects.
About This Site
This personal website serves as a repository for my replications of interesting studies/articles, analysis, and explorations of topics that spark my curiosity. As a data enthusiast, I enjoy diving into datasets, uncovering insights, and sharing my methods/findings - in as many coding languages as I possibly can.
On Replications: There has been a clear increase in the use of data ubiquitously and over recent years, news articles are therefore no exception. Embedded in news articles these days you can, and without much effort, find anything from simple tables to fairly involved/advanced visualizations. But of course, you seldom find the exact methodology the author(s) used in presenting said visualizations to their readers. The purpose here then becomes to reverse-engineer the final article output to generate a clear path to each ‘element’ that is required to make said outputs - almost like reconstructing a puzzle.
“Where there is a will, there is a way”; similarly, where there is HTML, there is its source page- less poetic but equally true. This will be the leitmotif for most data extraction from articles I work on replicating; unless they are behind a paywall (where an account has to be created first -with or without a paid subscription); or JS is intentionally set to not redirect; not allowing for the actual data to be revealed under the hood.
Along the way, I hope I do a good job explaining why I went with one method over another based on high certainty; meaning that this is what the author did as well; or purely making an educated guess, and then seeing how well the guessed method’s output matches the article’s. I find the exercise interesting for multiple reasons, one of which being thinking the same way the author thought so that both outputs align; that can be a useful learning experience for me and hopefully for you as well !
In terms of coding choices; I will mostly be using R in tandem with Quarto along with python and potentially explore additional languages/frameworks along the way.
On Analysis: I will likely begin devoting time to dive into articles or more generally online sources that I will either support or critique. This will be relying more on the analytical side of things in making my point of whether or not I think the article/piece drives home their point with rigor; and if not, suggest concrete improvements; be it on the choice of methods and/or how the message is conveyed visually.