So, I got this idea to mess around with some data about soccer fans. I’m no expert, just wanted to see what I could do, you know?
First, I had to find some data. That was a bit of a pain, honestly. I dug around online, and finally stumbled upon some datasets. It was a bit messy, all kinds of formats, some of it wasn’t even in English. Took a while to sort through it all, but I managed to pull together something usable.
Cleaning Up the Mess
Next, I had to clean up this data. Oh boy, was it a chore. There were missing values, incorrect entries, all sorts of junk. I spent a good chunk of time just going through it line by line, fixing things, making sure it all made sense. It felt like forever, but finally, I got it into a somewhat decent shape.
Figuring Out What to Do
Now, I had this clean-ish data, but what to do with it? I started thinking about what might be interesting to look at. Maybe see which countries had the most passionate fans? Or what age groups were most into soccer? I had a bunch of ideas, and some were, well, not so great. I ended up with some questions like these:
- Which teams are mentioned the most?
- What’s the general sentiment about different teams?
- Which countries have the most active fans?
I realized, that I have to visualize this data to get some answers. So, I used some tools to create some charts. I am no designer, the charts are not the best looking, but, hey, they got the job done.
The “Aha!” Moment
After all that tinkering, I finally started to see some interesting stuff. I could visualize which countries had the most fans, which leagues were the most popular, and even some basic sentiment analysis. Nothing groundbreaking, but I can see trends and patterns, and answer my own questions. For example, Fans from United Kingdom are mentioned the most!
It wasn’t easy, and my results aren’t going to win any awards, but it was a fun little project. I learned a lot, and it made me appreciate how much work goes into even simple data analysis. Maybe I’ll try something like this again sometime, but next time, I’m starting with cleaner data!
