Alright folks, let me tell you about this little project I was messing around with today: “davide astori.” Sounds kinda fancy, right? Well, it started pretty simple.
First thing I did was, I googled “davide astori” just to get my bearings. You know, see what’s out there. Found a bunch of stuff about the guy, obviously. Rest in peace.
Then, I thought, “Okay, what can I actually DO with this?” I decided to see if I could pull some data about his career. I figured I’d try scraping some football stats off a website. Found a decent-looking one with a bunch of Serie A info.
So, I fired up Python – my go-to for this kind of thing. Started with the basics: `requests` to grab the HTML and `BeautifulSoup` to parse it. Man, I always forget how messy website HTML can be. Spent a good chunk of time just figuring out the right CSS selectors to target the stats tables.
Once I had the data coming in, it was a lot of cleaning. You know, removing weird characters, converting strings to numbers, that kinda jazz. I ended up using `pandas` to structure it all into a nice, neat dataframe. Makes life so much easier.
After that, I wanted to visualize some of the data. Figured a simple line graph showing his appearances over the years would be cool. `matplotlib` to the rescue! It took a bit of tweaking to get the labels and axes looking right, but I got there eventually.
I even played around with trying to predict his future appearances (hypothetically, of course). Tried a few simple time series models using `statsmodels`. Didn’t get anything super accurate, but it was a fun exercise. Reminded me I need to brush up on my forecasting skills.
Finally, I just wrote up a little Markdown file summarizing what I did and included the graph and the code. Nothing fancy, but it’s a good record of the process.
Honestly, it was more about the journey than the destination. Just messing around with data, trying out different tools, and learning a few things along the way. That’s what it’s all about, right?