Okay, here’s my attempt to write a blog post about my experience with the “canadian women’s swim team” project, mimicking the requested style.
Diving Deep: My Canadian Women’s Swim Team Project
Alright, so I got this idea stuck in my head about the Canadian women’s swim team. I was watching the Olympics, and those ladies were just killing it. I thought, “Hey, I should try to build something… something related to them.” So, yeah, that’s how it started. Pretty random, I know.
First thing I did? Started Googling. Obvious, right? I just wanted to get a feel for the data out there, what was available, what could I even do with it. I spent a good chunk of an afternoon just bouncing around different sites, looking at team rosters, competition results, news articles, anything I could find.
Then came the scraping. Ugh. I found a couple of websites that had some decent data, but nothing was in a nice, neat format. So, I fired up Python and started wrestling with Beautiful Soup. Man, that was a pain. Figuring out the HTML structure, dealing with inconsistencies, cleaning up the data… it took way longer than I thought it would. I ended up writing a bunch of functions to handle different types of data and different website layouts.
Next up, I crammed all that scraped data into a CSV file. Simple, but effective. I used pandas to load it up. I did a lot of cleaning at this stage. Removing duplicates, standardizing names, converting datatypes. All that good stuff. Data cleaning is like 80% of any project, right? It felt like it, anyway.
Okay, so I had this big, messy CSV. Time to actually do something with it. I decided I wanted to visualize some stuff. I was thinking about things like medal counts over time, comparing individual swimmer’s performances, maybe even building a little interactive dashboard. I chose matplotlib and seaborn, cause I was already kinda familiar with them. Lots of tweaking and experimenting to get the charts looking how I wanted. Labels, titles, color palettes… it’s all about the details.
I even tried messing around with building a simple web app using Flask. The idea was to have a place where you could select a swimmer and see all their stats and results. Got the basic framework up and running, but then ran into some issues with deploying it. Turns out, getting a Flask app live on the internet is harder than it looks! I still want to figure that out, but I kinda ran out of steam.
- Data collection (scraping, CSV)
- Data cleaning (pandas)
- Visualization (matplotlib, seaborn)
- Basic web app (Flask)
In the end, I had a bunch of cool visualizations and a half-finished web app. Did I solve any world problems? Nah. But I learned a ton about web scraping, data analysis, and visualization. And, I got to learn more about the Canadian women’s swim team. They’re awesome!
Takeaway: Just start doing something. Don’t get bogged down in planning. Just pick a project, start coding, and figure it out as you go. You’ll learn way more that way.
