It’s been tricky keeping this series up! I’ve started learning about a lot of things at the same time and it’s been quite difficult to neatly isolate one bit to write about. A few weeks ago, however, I decided my social network analysis skills (or, as I like to call them here, my graph analysis skills – poor G was an unpopular letter while S was in high demand) needed a little refresher. I dedicated a big chunk of my Master’s degree last year to network analysis, and I loved it, but I hadn’t done anything in that space since. I mainly just wanted to check that I still had it – that I was still able to extract and build a network from messy social data without having a minor or major nervous breakdown. Continue Reading…

I’ve been quite excited to dive into web scraping. After all, my teenage self used to copy and paste HTML code like crazy to put together amateur website templates, and scraping is also maybe the most intuitive way of collecting data online – just grab what you see. In practice, it’s obviously a little trickier than that. Continue Reading…

I’m keeping it short & sweet this week; many of the letters I’ve chosen for this project will focus on machine learning algorithms in more detail, so here’s a tiny visual overview instead. For reference, I’m planning on watching all of these lovely lectures in the future and potentially invest in this book to get a little more grounding in the maths behind machine learning (hello darkness, my old friend).

One of the lovely things about this project is also that there’s no point in being a perfectionist; I won’t be able to produce flawless content every week, so it’s nice to embrace ‘good enough’, mix it up (like this week) and make it a priority to keep going. Continue Reading…

This last week, my programming brain has been all over the place. I’ve been looking into Natural Language Processing and trying to learn how to build a web application in Flask and it all felt like a huge complicated mess in my mind for most of the week. So I decided to turn to the familiar for comfort and kick off DIY Data Science with a topic that is near and dear to my heart – Pandas, Python’s superstar data analysis package.

Hello Pandas, my old friend

This is not the first time. Last December, after a few months of non-coding, I was desperate to get back into it. So my friend Zack offered to help me out and set me a little data cleaning and wrangling challenge to solve using Pandas. Continue Reading…

Recently, I’ve had a little bit of time to get back into coding and once again realised how much I enjoy it. Python is my language of choice, and I’m by no means an expert (though I’m pretty sure I can get there one day if I keep going). So far, I mostly focus on data collection, cleaning, analysis and visualisation. I only started coding a little over a year ago during my Masters degree; that is, if you don’t count my teenage self’s dabbling in HTML and CSS to make my first ever website look nice – yes, I was definitely one of the cool kids. Continue Reading…