Alright, so today I’m gonna walk you through this thing I was messing around with, kinda sparked by all the buzz around Grayson Murray and, well, you know, a certain former president. Don’t get me wrong, this isn’t about politics or golf gossip. It’s more about how I went down this rabbit hole trying to see if I could pull some interesting data using just their names as a starting point.
First off, I started super basic. I literally just Googled “grayson murray trump” and started clicking through the news articles, forum posts, anything that looked remotely interesting. I wasn’t looking for any specific outcome, just trying to see if there were any connections, any patterns that jumped out.
Then, I decided to try and get a bit more systematic. I figured, let’s try some data scraping. I ain’t no pro coder, mind you. So I used a free web scraper I found online – can’t remember the exact name, but there are tons of them out there. I targeted a few news sites and blogs that I knew often covered both golf and, uh, well, you know. The goal was to extract any sentences or paragraphs where both names appeared.
The scraping was messy, as you can imagine. Lots of garbage data, irrelevant stuff, but I eventually managed to clean it up a bit using some basic text editing tools. I’m talking find and replace, deleting entire chunks of HTML code, the whole shebang. Pretty tedious, but necessary.
Next up, I decided to see if I could visualize the data somehow. I dumped all the extracted text into a simple word cloud generator. It was pretty basic, but it gave me a quick overview of the most frequently used words alongside “Grayson Murray” and “Trump.” Words like “golf,” “tournament,” and a few other relevant terms popped up, which wasn’t exactly earth-shattering, but it was a start.
I also messed around with trying to find any overlap in their social media followings. I used a couple of free tools that analyze Twitter (I know, I know, it’s X now, but old habits die hard) accounts and identify shared followers. Didn’t find anything super significant, but there was a small percentage of accounts that followed both. Could be bots, could be genuine fans, who knows?
To be honest, the whole exercise was more about learning and experimenting than uncovering some hidden truth. I didn’t find any smoking gun or major revelation. But I did get a better feel for how to scrape data, clean it up, and visualize it in a basic way. Plus, it was a fun way to spend an afternoon, diving into the weird and wonderful world of online data.
Key Takeaways:
- Starting with a simple Google search is always a good first step.
- Free web scraping tools are your friend (but be prepared to clean up a lot of junk).
- Word clouds are a quick and dirty way to visualize text data.
- Don’t expect to find groundbreaking insights every time – sometimes it’s just about the process.
So yeah, that’s my “grayson murray trump” data adventure. Nothing too crazy, but hopefully, it gives you some ideas for your own data-diving experiments!